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  • 1.
    Hlawitschka, Mario
    et al.
    Department of Computer Science, Leipzig University, Germany.
    Hotz, Ingrid
    Zuse Institue Berlin, Germany.
    Kratz, Andrea
    Zuse Institue Berlin, Germany.
    Marai, G. Elisabeta
    Department of Computer Science, University of Pittsburgh, USA.
    Moreno, Rodrigo
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Scheuermann, Gerik
    Department of Computer Science, Leipzig University, Germany.
    Strommel, Markus
    Chair of Polymer Materials, Saarland University, Saarbruecken, Germany.
    Wiebel, Alexander
    Department of Electrical Engineering and Computer Sciences, Coburg University of Applied Sciences, Germany.
    Zhang, Eugene
    School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, USA.
    Top Challenges in the Visualization of Engineering Tensor Fields2014Inngår i: Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data / [ed] Carl-Fredrik Westin, Anna Vilanova, Bernhard Burgeth, Springer Berlin/Heidelberg, 2014, s. 3-15Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    In this chapter we summarize the top research challenges in creating successful visualization tools for tensor fields in engineering. The analysis is based on our collective experiences and on discussions with both domain experts and visualization practitioners. We find that creating visualization tools for engineering tensors often involves solving multiple different technical problems at the same time—including visual intuitiveness, scalability, interactivity, providing both detail and context, integration with modeling and simulation, representing uncertainty and managing multi-fields; as well as overcoming terminology barriers and advancing research in the mathematical aspects of tensor field processing. We further note the need for tools and data repositories to encourage faster advances in the field. Our interest in creating and proposing this list is to initiate a discussion about important research issues within the visualization of engineering tensor fields.

  • 2.
    Julià, Carme
    et al.
    Rovira i Virgili University, Spain.
    Moreno, Rodrigo
    Rovira i Virgili University, Spain.
    Puig, Domenec
    Rovira i Virgili University, Spain.
    Garcia, Miguel Angel
    Autonomous University of Madrid, Spain.
    Shape-based image segmentation through photometric stereo2011Inngår i: Computer Vision and Image Understanding, ISSN 1077-3142, E-ISSN 1090-235X, Vol. 115, nr 1, s. 91-104Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper describes a new algorithm for segmenting 2D images by taking into account 3D shape information. The proposed approach consists of two stages. In the first stage, the 3D surface normals of the objects present in the scene are estimated through robust photometric stereo. Then, the image is segmented by grouping its pixels according to their estimated normals through graph-based clustering. One of the advantages of the proposed approach is that, although the segmentation is based on the 3D shape of the objects, the photometric stereo stage used to estimate the 3D normals only requires a set of 2D images. This paper provides an extensive validation of the proposed approach by comparing it with several image segmentation algorithms. Particularly, it is compared with both appearance-based image segmentation algorithms and shape-based ones. Experimental results confirm that the latter are more suitable when the objective is to segment the objects or surfaces present in the scene. Moreover, results show that the proposed approach yields the best image segmentation in most of the cases.

  • 3.
    Kirişli, Hortense
    et al.
    Erasmus MC, Rotterdam, The Netherlands.
    Schaap, M.
    Erasmus MC, Rotterdam, The Netherlands.
    Metz, C. T.
    Erasmus MC, Rotterdam, The Netherlands.
    Dharampal, A. S.
    Erasmus MC, Rotterdam, The Netherlands.
    Meijboom, W. B.
    Erasmus MC, Rotterdam, The Netherlands.
    Papadopoulou, S. L.
    Erasmus MC, Rotterdam, The Netherlands.
    Dedic, A.
    Erasmus MC, Rotterdam, The Netherlands.
    Nieman, K.
    Erasmus MC, Rotterdam, The Netherlands.
    de Graaf, M. A.
    Leiden UMC, The Netherlands.
    Meijs, M. F. L.
    UMC Utrecht, The Netherlands.
    Cramer, M. J.
    UMC Utrecht, The Netherlands.
    Broersen, A.
    Leiden UMC, The Netherlands.
    Cetin, S.
    SabancıUniversity, Turkey.
    Eslami, A.
    Technical University of Munich, Germany.
    Flórez-Valencia, L.
    Pontificia Universidad Javeriana, Bogotá, Colombia.
    Lor, K.L.
    National Taiwan University, Taipei, Taiwan.
    Matuszewski, B.
    University of Central Lancashire, Preston, UK.
    Melki, I.
    Université Paris-Est, France.
    Mohr, B.
    Toshiba Medical Visualization Systems, Edinburgh, UK.
    Öksüz, I.
    Bahçeşehir University, Istanbul, Turkey.
    Shahzad, R.
    Erasmus MC, Rotterdam The Netherlands.
    Wang, Chunliang
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Kitslaar, P. H.
    Leiden UMC, The Netherlands.
    Unal, G.
    Sabancı University, Turkey.
    Katouzian, A.
    Technical University of Munich, Germany.
    Orkisz, M.
    Université de Lyon, France.
    Chen, C.M.
    National Taiwan University, Taipei, Taiwan.
    Precioso, F.
    University Nice-Sophia Antipolis, France.
    Najman, L.
    Université Paris-Est, France.
    Masood, S.
    Toshiba Medical Visualization Systems, Edinburgh, UK.
    Ünay, D.
    Bahçeşehir University, Istanbul, Turkey.
    van Vliet, L.
    Delft University of Technology, The Netherlands.
    Moreno, Rodrigo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Goldenberg, R.
    Rcadia Medical Imaging, Haïfa, Israel.
    Vuçini, E.
    VRVis Research Center for Virtual Reality and Visualization, Vienna, Austria.
    Krestin, G. P.
    Erasmus MC, Rotterdam, The Netherlands.
    Niessen, W. J.
    Erasmus MC, Rotterdam, The Netherlands.
    van Walsum, T.
    Erasmus MC, Rotterdam, The Netherlands.
    Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography2013Inngår i: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 17, nr 8, s. 859-876Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Though conventional coronary angiography (CCA) has been the standard of reference for diagnosing coronary artery disease in the past decades, computed tomography angiography (CIA) has rapidly emerged, and is nowadays widely used in clinical practice. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms devised to detect and quantify the coronary artery stenoses, and to segment the coronary artery lumen in CIA data. The objective of this evaluation framework is to demonstrate the feasibility of dedicated algorithms to: (I) (semi-)automatically detect and quantify stenosis on CIA, in comparison with quantitative coronary angiography (QCA) and CIA consensus reading, and (2) (semi-)automatically segment the coronary lumen on CIA, in comparison with expert's manual annotation. A database consisting of 48 multicenter multivendor cardiac CIA datasets with corresponding reference standards are described and made available. The algorithms from 11 research groups were quantitatively evaluated and compared. The results show that (1) some of the current stenosis detection/quantification algorithms may be used for triage or as a second-reader in clinical practice, and that (2) automatic lumen segmentation is possible with a precision similar to that obtained by experts. The framework is open for new submissions through the website, at http://coronary.bigr.nl/stenoses/.

  • 4.
    Klintström, Eva
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten.
    Klintström, Benjamin
    Linköpings universitet, Institutionen för medicin och hälsa. Linköpings universitet, Medicinska fakulteten.
    Brismar, Torkel
    Karolinska Institutet, Stockholm, Sweden.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping. KTH Royal Institute of Technology, Stockholm, Sweden.
    Moreno, Rodrigo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. KTH Royal Institute of Technology, Stockholm, Sweden.
    Clinical dental cone beam computed tomography - a tool for monitoring trabecular bone structure?2015Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Purpose

    The aim of this in vitro study was to develop a method for quantitative assessment of trabecular bone micro-architecture by using three-dimensional image processing. The imaging data were acquired with cone beam computed tomography (CBCT), traditionally used for facial and temporal bone imaging but also applicable for peripheral skeleton, and with a dedicated high resolution peripheral computed tomograph (HRpQCT), used for in vivo measurements in bone research. The data from micro-computed tomography (µCT) was used as reference.

     

    Methods & Materials

    15 bone samples from the radius, were examined by CBCT and HRpQCT at a resolution of 80 and 82 µm, respectively. After segmentation, the bone structure parameters bone volume (BV/TV), trabecular thickness (Tb.Th), trabecular separation (Tb.Sp), trabecular number (Tb.N), trabecular nodes (Tb.Nd) and trabecular termini (Tb.Tm) were quantified. Calculations were performed on an ordinary PC using a MATLAB developed in house.

     

    Results

    CBCT and HRpQCT overestimated BV/TV and Tb.Th approximately three times, compared to µCT. On the other hand Tb.Nd was highly underestimated. All parameters from CBCT were strongly correlated to µCT, with correlation coefficients above 0.91 for all studied parameters (0.92-0.98) except for Tb.Tm with a correlation of 0.83. For HRpQCT the correlations were slightly weaker, varying from 0.78 to 0.95.

     

    Conclusion

    The strong correlations between bone structure parameters computed from CBCT and µCT suggests that CBCT may be a good alternative to HRpQCT for monitoring trabecular bone microarchitecture in vivo.

     

  • 5.
    Klintström, Eva
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Moreno, Rodrigo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Brismar, Torkel
    Karolinska University Hospital, Stockholm, Sweden.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Three-dimensional image processing for measuring trabecular bone structure parameters2012Konferansepaper (Annet vitenskapelig)
  • 6.
    Klintström, Eva
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Moreno, Rodrigo
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Brismar, Torkel
    Karolinska Institutet, Stockholm, Sweden.
    Smedby, Örjan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Trabecular bone structure parameters from cone beam computed tomography data2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    15 bone samples from the radius were examined by CBCT. Micro CT wasused as reference when quantifying trabecular bone structures. All parameters from CBCTwere strongly correlated to μCT, with correlation above 0.90. CBCT overestimated BV/TV andTb.Th more than three times compared to μCT. Tb.Nd, Tb.Sp and Tb.N were underestimated.

  • 7.
    Klintström, Eva
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Smedby, Örjan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Klintström, Benjamin
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Brismar, Torkel
    Karolinska University Hospital Huddinge, Stockholm, Sweden.
    Moreno, Rodrigo
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Trabecular bone histomorphometric measurements and contrast-to-noise ratio in CBCT2014Inngår i: Dento-Maxillo-Facial Radiology, ISSN 0250-832X, E-ISSN 1476-542X, Vol. 43, nr 8, s. 20140196-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Objectives: The aim of this study was to evaluate how imaging parameters at clinical dental CBCT affect the accuracy in quantifying trabecular bone structures, contrast-to-noise ratio (CNR) and radiation dose.

    Methods: 15 radius samples were examined using CBCT (Accuitomo FPD; J. Morita Mfg., Kyoto, Japan). Nine imaging protocols were used, differing in current, voltage, rotation degree, voxel size, imaging area and rotation time. Radiation doses were measured using a KAP-meter. After segmentation, six bone structure parameters and CNR were quantified. Micro-CT images with an isotropic resolution of 20 microns were used as a gold standard.

    Results: Structure parameters obtained by CBCT were strongly correlated to those by micro CT, with correlation coefficients .0.90 for all studied parameters. Bone volume and trabecular thickness were not affected by changes in imaging parameters. Increased tube current from 5 to 8 mA, decreased isotropic voxel size from 125 to 80 microns and decreased rotation anglefrom 360° to 180° affected correlations for trabecular termini negatively. Decreasing rotation degree also weakened correlations for trabecular separation and trabecular number at 80 microns voxel size. Changes in the rotation degree and tube current affected CNR significantly. The radiation dose varied between 269 and 1284 mGy cm2.

    Conclusions: Trabecular bone structure can be accurately quantified by clinical dental CBCT in vitro, and the obtained structure parameters are strongly related to those obtained by micro CT. A fair CNR and strong correlations can be obtained with a low radiation dose, indicating the possibility for monitoring trabecular bone structure also in vivo.

  • 8.
    Klintström, Eva
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Moreno, Rodrigo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Brismar, Torkel
    Karolinska University Hospital, Stockholm, Sweden.
    Trabecular bone structure parameters from 3D image processing of clinical multi-slice and cone-beam computed tomography data2014Inngår i: Skeletal Radiology, ISSN 0364-2348, E-ISSN 1432-2161, Vol. 43, nr 2, s. 197-204Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Objective

    Bone strength depends on both mineral content and bone structure. The aim of this in vitro study was to develop a method of quantitatively assessing trabecular bone structure by applying three-dimensional image processing to data acquired with multi-slice and cone-beam computed tomography using micro-computed tomography as a reference.

    Materials and Methods

    Fifteen bone samples from the radius were examined. After segmentation, quantitative measures of bone volume, trabecular thickness, trabecular separation, trabecular number, trabecular nodes, and trabecular termini were obtained.

    Results

    The clinical machines overestimated bone volume and trabecular thickness and underestimated trabecular nodes and number, but cone-beam CT to a lesser extent. Parameters obtained from cone beam CT were strongly correlated with μCT, with correlation coefficients between 0.93 and 0.98 for all parameters except trabecular termini.

    Conclusions

    The high correlation between cone-beam CT and micro-CT suggest the possibility of quantifying and monitoring changes of trabecular bone microarchitecture in vivo using cone beam CT.

  • 9.
    Koppal, Sandeep
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Hälsouniversitetet.
    Moreno, Rodrigo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Dyverfeldt, Petter
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Hälsouniversitetet.
    Warntjes, Marcel
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Hjärt- och Medicincentrum, Fysiologiska kliniken US.
    de Muinck, Ebo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Hälsouniversitetet.
    Optimal validering av MR-bildtagning av aterosklerotiska plack genom användning av multi-modal MR och 3D histologi2013Konferansepaper (Annet vitenskapelig)
    Abstract [sv]

    BAKGRUND: Magnetkamera (MR) kan identifiera aterosklerotiska plack som löper risk att brista och därmed orsaka stroke eller hjärtinfarkt. Metoden är dock bristfälligt validerad på grund av den osäkerhet som uppstår då 2D histologiska snitt ska registreras med 3D MR-bilder.

    SYFTE: Att optimera validering av MR-bildtagning av aterosklerotiska plack genom användning av multi-modal MR och 3D histologi.

    MATERIAL och METOD: Patienter som skulle opereras för att avlägsna aterosklerotiska plack från arteria karotis genomgick dedikerad plack-MR där följande parametrar undersöktes: plackets fettinnehåll, blödning inuti placket och maximal intensitet av turbulent blodflöde. Undersökningarna gjordes med en Philips 3T MR-kamera: (a) 4-punkt Dixon 3D gradient-eko, (b) T1-viktad spin-eko, (c) 4D fas-kontrast. Upplösningen var 0.6x0.6x0.7mm, 0.35x0.35x3mm respektive 1.14x1.25x1.14mm x 25ms. Vatten-, fett- and R2*-bilder (blödning) beräknades utifrån Dixon-sekvensen.Efter operation bäddades placken in i paraffin och enface-bilder togs varje 50µm i Z-riktning. Bilderna registrerades i ImageJ/Fiji och användes för att bygga en 3D-volym av placket. Vid varje 200µm togs snitt för biologiska markörer och histologiska färgningar. De färgade snitten registrerades med motsvarande enface-bilder. Detta resulterade i 3D-volymer med en upplösning på 1.02x1.02x200µm. Den histologiska 3D-volymen registrerades manuellt med uppsamplade och co-registrerade MR-bilder.

    RESULTAT: T1-viktade bilder var bäst för registrering av plack inom varje snitt. Registrering av kärlets lumen optimerades genom en kombination av 4D fas-kontrast, det första Dixon-ekot och vatten-bilder. Registrering av fett och R2* från MR-bilder med fett och blödning från 3D histologi uppvisade god överensstämmelse.

    SLUTSATS: Optimal validering av MR-bilder av aterosklerotiska plack kan åstadkommas genom att kombinera olika anatomiska landmärken från multimodala MR-bilder av plack och 3D-histologi. Genom att använda 3D-histologi korrigerar man för registreringsproblem som är relaterade till ”out-of-plane” vinklingar av vävnadssnitt och krympning och deformering till följd av histologiskt bearbetning av placket. Den detaljerade biologiska informationen från 3D-histologi kan förväntas förstärka fynden från in vivo MR-bilder.

  • 10.
    Koppal, Sandeep
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten.
    Warntjes, Marcel
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Hjärt- och Medicincentrum, Fysiologiska kliniken US. SyntheticMR AB, Linköping, Sweden.
    Swann, Jeremy
    School of Computing, University of Leeds, Leeds, United Kingdom.
    Dyverfeldt, Petter
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Hjärt- och Medicincentrum, Fysiologiska kliniken US.
    Kihlberg, Johan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten.
    Moreno, Rodrigo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. KTH, Royal Institute of Technology, Stockholm, Sweden.
    Magee, Derek
    School of Computing, University of Leeds, Leeds, United Kingdom.
    Roberts, Nicholas
    Division of Brain Sciences, Department of Medicine, Institute of Neurology, Imperial College, London, United Kingdom.
    Zachrisson, Helene
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Hjärt- och Medicincentrum, Fysiologiska kliniken US.
    Forssell, Claes
    Region Östergötland, Hjärt- och Medicincentrum, Thorax-kärlkliniken i Östergötland.
    Länne, Toste
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Hjärt- och Medicincentrum, Thorax-kärlkliniken i Östergötland.
    Treanor, Darren
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för neuro- och inflammationsvetenskap. Linköpings universitet, Medicinska fakulteten. Department of Pathology and Tumour Biology, Leeds Institute of Molecular Medicine, University of Leeds, Leeds, United Kingdom.
    de Muinck, Ebo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Hjärt- och Medicincentrum, Kardiologiska kliniken US.
    Quantitative Fat and R2* Mapping In Vivo to Measure Lipid-Rich Necrotic Core and Intraplaque Hemorrhage in Carotid Atherosclerosis2017Inngår i: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 78, nr 1, s. 285-296Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Purpose: The aim of this work was to quantify the extent of lipid-rich necrotic core (LRNC) and intraplaque hemorrhage (IPH) in atherosclerotic plaques.

    Methods: Patients scheduled for carotid endarterectomy underwent four-point Dixon and T1-weighted magnetic resonance imaging (MRI) at 3 Tesla. Fat and R2* maps were generated from the Dixon sequence at the acquired spatial resolution of 0.60 × 0.60 × 0.70 mm voxel size. MRI and three-dimensional (3D) histology volumes of plaques were registered. The registration matrix was applied to segmentations denoting LRNC and IPH in 3D histology to split plaque volumes in regions with and without LRNC and IPH.

    Results: Five patients were included. Regarding volumes of LRNC identified by 3D histology, the average fat fraction by MRI was significantly higher inside LRNC than outside: 12.64 ± 0.2737% versus 9.294 ± 0.1762% (mean ± standard error of the mean [SEM]; P < 0.001). The same was true for IPH identified by 3D histology, R2* inside versus outside IPH was: 71.81 ± 1.276 s−1 versus 56.94 ± 0.9095 s−1 (mean ± SEM; P < 0.001). There was a strong correlation between the cumulative fat and the volume of LRNC from 3D histology (R2 = 0.92) as well as between cumulative R2* and IPH (R2 = 0.94).

    Conclusion: Quantitative mapping of fat and R2* from Dixon MRI reliably quantifies the extent of LRNC and IPH.

  • 11.
    Moreno, Rodrigo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Management of the Level of Coursework in PhD Education: A Case of Sweden2014Inngår i: Journal of Applied Economics and Business Research, ISSN 1927-033X, E-ISSN 1927-033X, Vol. 4, nr 3, s. 168-177Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    PhD programs around the world include a variable amount of coursework. Using a curriculum design perspective, this paper explores the pros and cons of using different levels of coursework in PhD education. Inefficient management of coursework can jeopardize the quality of the PhD programs, since the students will be forced to devote less time to their research. On the contrary, coursework can also become a powerful teaching and learning activity that can help the PhD students to attain the intended learning outcomes of the program. However, a deep involvement of the administration and supervisors in the design of coursework is necessary for the latter case. Although the paper uses the Swedish system as a reference, most of the discussion is well applicable to most PhD programs elsewhere.

  • 12.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Filosofiska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Klintström, Eva
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Brismar, Torkel
    Department of Radiology, Karolinska University Hospital at Huddinge, Huddinge, Sweden.
    Smedby, Örjan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Anisotropy Estimation of Trabecular Bone in Gray-Scale: Comparison Between Cone Beam and Micro Computed Tomography Data2015Inngår i: Developments in Medical Image Processing and Computational Vision / [ed] João Manuel R.S. Tavares and Renato Natal Jorge, Springer, 2015, s. 207-220Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    Measurement of anisotropy of trabecular bone has clinical relevance in osteoporosis. In this study, anisotropy measurements of 15 trabecular bone biopsies from the radius estimated by different fabric tensors on images acquired through cone beam computed tomography (CBCT) and micro computed tomography (micro-CT) were compared. The results show that the generalized mean intercept length (MIL) tensor performs better than the global gray-scale structure tensor, especially when the von Mises-Fisher kernel is applied. Also, the generalized MIL tensor yields consistent results between the two scanners. These results suggest that this tensor is appropriate for estimating anisotropy in images acquired in vivo through CBCT. 

  • 13.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Borga, Magnus
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Klintström, Eva
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Brismar, Torkel
    Karolinska Institutet University Hospital, Stockholm, Sweden.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Correlations between fabric tensors computed on cone beam and microcomputed tomography images2014Inngår i: Computational Vision and Medical Image Processing IV: Proceedings of Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013 / [ed] Manuel J.,Tavares R.S.,Jorge R.M.N., CRC Press, 2014, s. 393-398Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Computational Vision and Medical Image Processing. VIPIMAGE 2013

    contains invited lectures and full papers presented at VIPIMAGE 2013 - IV ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing (Funchal, Madeira Island, Portugal, 14-16 October 2013). International contributions from 16 countries provide a comprehensive coverage of the current state-of-the-art in the fields of: 3D Vision; Computational Bioimaging and Visualization; Computational Vision and Image Processing applied to Dental Medicine; Computational Vision; Computer Aided Diagnosis, Surgery, Therapy, and Treatment; Data Interpolation, Registration, Acquisition and Compression; Image Processing and Analysis; Image Segmentation; Imaging of Biological Flows; Medical Imaging; Physics of Medical Imaging; Shape Reconstruction; Signal Processing; Simulation and Modeling; Software Development for Image Processing and Analysis; Telemedicine Systems and their Applications; Trabecular Bone Characterization; Tracking and Analysis of Movement; Virtual Reality.

    Related techniques covered in this book include the level set method, finite element method, modal analyses, stochastic methods, principal and independent components analysis and distribution models. Computational Vision and Medical Image Processing. VIPIMAGE 2013 is useful to academics, researchers and professionals in Biomechanics, Biomedical Engineering, Computational Vision (image processing and analysis), Computer Sciences, Computational Mechanics and Medicine.

  • 14.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Borga, Magnus
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Estimation of Trabecular Thickness in Gray-Scale Images Through Granulometric Analysis2012Inngår i: Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 2012Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    This paper extends to gray-scale the method proposed by Hildebrand and Ru ̈egsegger for estimating thickness of trabecular bone, which is the most used in trabecular bone research, where local thickness at a point is defined as the diameter of the maximum inscribed ball that includes that point. The proposed extension takes advantage of the equivalence between this method and the opening function computed for the granulometry generated by the opening operation of mathematical morphology with ball-shaped structuring elements of different radii. The proposed extension (a) uses gray-scale instead of binary mathematical morphology, (b) uses all values of the pattern spectrum of the granulometry instead of the maximum peak as used for binary images, (c) corrects bias on local thickness estimations generated by partial volume effects, and (d) uses the gray-scale as a weighting function for global thickness estimation. The proposed extension becomes equivalent to the original method when it is applied to binary images. A new non-flat structuring element is also proposed in order to reduce the discretization errors generated by traditional flat structuring elements. Translation invariance can be attained by up-sampling the images through interpolation by a factor of two. Results for synthetic and real images show that the quality of the measurements obtained through the original method strongly depend on the binarization process, whereas the measurements obtained through the proposed extension does not. Consequently, the proposed extension is more appropriate for images with limited resolution where binarization is not trivial. 

  • 15.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa. Linköpings universitet, Tekniska högskolan.
    Borga, Magnus
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Evaluation of the plate-rod model assumption of trabecular bone2012Inngår i: 9th IEEE International Symposium on Biomedical Imaging (ISBI), 2012, IEEE Press, 2012, s. 470-473Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Trabecular bone has traditionally been assumed to be composed of plate- and rod-like trabeculae. This paper proposes a method to numerically evaluate the appropriateness of this assumption. In a first step, local constancy of thickness is estimated by comparing the maximum and mean diameter of the maximum inscribed balls centered at the medial axis/surface that includes every local point. In a second step, deviations from null curvature at the medial axis/surface are locally measured by comparing the geodesic and Euclidean distances from a point to its neighbors in the medial axis/surface. Finally, these two measurements are combined in order to locally estimate the compliance of the dataset with the plate-rod model assumption. Experiments on synthetic datasets show that the proposed measurements can be used to decide the compliance of a 3D shape with the plate-rod model. Results on micro computed tomography images show that the plate-rod model is more valid for a vertebra than for a radius. Thus, especially for the radius, measurements based on this model should be complemented with the proposed measurements.

  • 16.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Borga, Magnus
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Generalizing the mean intercept length tensor for gray-level images2012Inngår i: Medical physics (Lancaster), ISSN 0094-2405, Vol. 39, nr 7, s. 4599-4612Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Purpose: The mean intercept length tensor is the most used technique to estimate microstructure orientation and anisotropy of trabecular bone. This paper proposes an efficient extension of this technique to gray-scale images based on a closed formulation of the mean intercept length tensor and a generalization using different angular convolution kernels.

    Methods: First, the extended Gaussian image is computed for the binary or gray-scale image. Second, the intercepts are computed for all possible orientations through an angular convolution with the half-cosine function. Finally, the tensor is computed by means of the covariance matrix. The complexity of the method is O(n + m) in contrast with O(nm) of traditional implementations, where n is the number of voxels in the image and m is the number of orientations used in the computations. The method is generalized by applying other angular convolution kernels instead of the half-cosine function. As a result, the anisotropy of the tensor can be controlled while keeping the eigenvectors intact.

    Results: The proposed extension to gray-scale yields accurate results for reliable computations of the extended Gaussian image and, unlike the traditional methodology, is not affected by artifacts generated by discretizations during the sampling of different orientations.

    Conclusions: Experiments show that the computations on both binary and gray-scale images are correlated, and that computations in gray-scale are more robust, enabling the use of the mean intercept length tensor to clinical examinations of trabecular bone. The use of kernels based on the von Mises-Fisher distribution is promising as the anisotropy can be adjusted with a parameter in order to improve its power to predict mechanical properties of trabecular bone.

  • 17.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska högskolan.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska högskolan.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Tekniska högskolan. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Soft classification of trabeculae in trabecular bone2011Inngår i: Biomedical Imaging: From Nano to Macro, 2011, IEEE , 2011, s. 1641-1644Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Classification of trabecular bone aims at discriminating different types of trabeculae. This paper proposes a method to perform a soft classification from binary 3D images. In a first step, the local structure tensor is used to estimate a membership degree of every voxel to three different classes, plate-, rod- and junction-like trabeculae. In a second step, the global structure tensor of plate-like trabeculae is compared with the local orientation of rod-like trabeculae in order to discriminate aligned from non-aligned rods. Results show that soft classification can be used for estimating independent parameters of trabecular bone for every different class, by using the classification as a weighting function.

  • 18.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Smedby, Örjan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Techniques for Computing Fabric Tensors: A Review2014Inngår i: Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data / [ed] Carl-Fredrik Westin, Anna Vilanova, Bernhard Burgeth, Springer Berlin/Heidelberg, 2014, s. 271-292Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    The aim of this chapter is to review different approaches that have been proposed to compute fabric tensors with emphasis on trabecular bone research. Fabric tensors aim at modeling through tensors both anisotropy and orientation of a material with respect to another one. Fabric tensors are widely used in fields such as trabecular bone research, mechanics of materials and geology. These tensors can be seen as semi-global measurements since they are computed in relatively large neighborhoods, which are assumed quasi-homogeneous. Many methods have been proposed to compute fabric tensors. We propose to classify fabric tensors into two categories: mechanics-based and morphology-based. The former computes fabric tensors from mechanical simulations, while the latter computes them by analyzing the morphology of the materials. In addition to pointing out advantages and drawbacks for each method, current trends and challenges in this field are also summarized.

  • 19.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Garcia, Miguel Angel
    Autonomous University of Madrid, Spain.
    Puig, Domenec
    Rovira i Virgili University, Spain.
    Tensor Voting for Robust Color Edge Detection2014Inngår i: Advances in Low-Level Color Image Processing / [ed] M. Emre Celebi and Bogdan Smolka, Springer Netherlands, 2014, s. 279-301Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    This chapter proposes two robust color edge detection methods based on tensor voting. The first method is a direct adaptation of the classical tensor voting to color images where tensors are initialized with either the gradient or the local color structure tensor. The second method is based on an extension of tensor voting in which the encoding and voting processes are specifically tailored to robust edge detection in color images. In this case, three tensors are used to encode local CIELAB color channels and edginess, while the voting process propagates both color and edginess by applying perception-based rules. Unlike the classical tensor voting, the second method considers the context in the voting process. Recall, discriminability, precision, false alarm rejection and robustness measurements with respect to three different ground-truths have been used to compare the proposed methods with the state-of-the-art. Experimental results show that the proposed methods are competitive, especially in robustness. Moreover, these experiments evidence the difficulty of proposing an edge detector with a perfect performance with respect to all features and fields of application.

  • 20.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Garcia, Miguel Angel
    Department of Informatics Engineering, Autonomous University of Madrid, Madrid, Spain.
    Puig, Domenec
    Intelligent Robotics and Computer Vision Group at the Department of Computer Science and Mathematics, Rovira i Virgili University, Tarragona, Spain.
    Julià, Carme
    Intelligent Robotics and Computer Vision Group at the Department of Computer Science and Mathematics, Rovira i Virgili University, Tarragona, Spain.
    Edge-Preserving Color Image Denoising Through Tensor Voting2011Inngår i: Computer Vision and Image Understanding, ISSN 1077-3142, E-ISSN 1090-235X, Vol. 115, nr 11, s. 1536-1551Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper presents a new method for edge-preserving color image denoising based on the tensor voting framework, a robust perceptual grouping technique used to extract salient information from noisy data. The tensor voting framework is adapted to encode color information through tensors in order to propagate them in a neighborhood by using a specific voting process. This voting process is specifically designed for edge-preserving color image denoising by taking into account perceptual color differences, region uniformity and edginess according to a set of intuitive perceptual criteria. Perceptual color differences are estimated by means of an optimized version of the CIEDE2000 formula, while uniformity and edginess are estimated by means of saliency maps obtained from the tensor voting process. Measurements of removed noise, edge preservation and undesirable introduced artifacts, additionally to visual inspection, show that the proposed method has a better performance than the state-of-the-art image denoising algorithms for images contaminated with CCD camera noise.

  • 21.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Garcia, Miguel Angel
    Autonomous University of Madrid, Spain.
    Puig, Domenec
    Rovira i Virgili University, Tarragona, Spain.
    Pizarro, Luis
    Imperial College London, UK.
    Burgeth, Bernhard
    Saarland University, Saarbrücken, Germany.
    Weickert, Joachim
    Saarland University, Saarbrücken, Germany.
    On improving the efficiency of tensor voting2011Inngår i: IEEE Transaction on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, E-ISSN 1939-3539, Vol. 33, nr 11, s. 2215-2228Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper proposes two alternative formulations to reduce the high computational complexity of tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. The first scheme consists of numerical approximations of the votes, which have been derived from an in-depth analysis of the plate and ball voting processes. The second scheme simplifies the formulation while keeping the same perceptual meaning of the original tensor voting: The stick tensor voting and the stick component of the plate tensor voting must reinforce surfaceness, the plate components of both the plate and ball tensor voting must boost curveness, whereas junctionness must be strengthened by the ball component of the ball tensor voting. Two new parameters have been proposed for the second formulation in order to control the potentially conflictive influence of the stick component of the plate vote and the ball component of the ball vote. Results show that the proposed formulations can be used inapplications where efficiency is an issue since they have a complexity of order O(1). Moreover, the second proposed formulation has been shown to be more appropriate than the original tensor voting for estimating saliencies by appropriately setting the two new parameters.

  • 22.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Koppal, Sandeep
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Hälsouniversitetet.
    de Muinck, Ebo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för kardiovaskulär medicin. Linköpings universitet, Hälsouniversitetet.
    Robust Estimation of Distance Between Sets of Points2013Inngår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 34, nr 16, s. 2192-2198Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper proposes a new methodology for computing Hausdorff distances between sets of points in a robust way. In a first step, robust nearest neighbor distance distributions between the two sets of points are obtained by considering reliability measures in the computations through a Monte Carlo scheme. In a second step, the computed distributions are operated using random variables algebra in order to obtain probability distributions of the average, minimum or maximum distances. In the last step, different statistics are computed from these distributions. A statistical test of significance, the nearest neighbor index, in addition to the newly proposed divergence and clustering indices are used to compare the computed measurements with respect to values obtained by chance. Results on synthetic and real data show that the proposed method is more robust than the standard Hausdorff distance. In addition, unlike previously proposed methods based on thresholding, it is appropriate for problems that can be modeled through point processes.

  • 23.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Pizarro, Luis
    Imperial College London, Department of Computing, UK.
    Burgeth, Bernhard
    Saarland University, Faculty of Mathematics and Computer Science, Germany.
    Weickert, Joachim
    Saarland University, Faculty of Mathematics and Computer Science, Germany .
    Garcia, Miguel Angel
    Autonomous University of Madrid, Department of Electronic and Communications Technology, Spain.
    Puig, Domenec
    Rovira i Virgili University, Department of Computer Science and Mathematics, Spain.
    Adaptation of Tensor Voting to Image Structure Estimation2012Inngår i: New Developments in the Visualization and Processing of Tensor Fields / [ed] David Laidlaw and Anna Vilanova, Springer Berlin/Heidelberg, 2012, s. 29-50Kapittel i bok, del av antologi (Annet vitenskapelig)
    Abstract [en]

    Bringing together key researchers in disciplines ranging from visualization and image processing to applications in structural mechanics, fluid dynamics, elastography, and numerical mathematics, the workshop that generated this edited volume was the third in the successful Dagstuhl series. Its aim, reflected in the quality and relevance of the papers presented, was to foster collaboration and fresh lines of inquiry in the analysis and visualization of tensor fields, which offer a concise model for numerous physical phenomena. Despite their utility, there remains a dearth of methods for studying all but the simplest ones, a shortage the workshops aim to address.Documenting the latest progress and open research questions in tensor field analysis, the chapters reflect the excitement and inspiration generated  by this latest Dagstuhl workshop, held in July 2009. The topics they address range from applications of the analysis of tensor fields to purer research into their mathematical and analytical properties. They show how cooperation and the sharing of ideas and data between those engaged in pure and applied research can open new vistas in the study of tensor fields

  • 24.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa. Linköpings universitet, Hälsouniversitetet.
    Romu, Thobias
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Dahlqvist Leinhard, Olof
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Centrum för kirurgi, ortopedi och cancervård, Radiofysikavdelningen US.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    de Muinck, Ebo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa. Linköpings universitet, Hälsouniversitetet.
    Effects of denoising in the estimation of T2* from images acquired through Dixon imaging2013Konferansepaper (Annet vitenskapelig)
  • 25.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. KTH Royal Institute of Technology.
    Smedby, Örjan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping. Linköpings universitet, Medicinska fakulteten. KTH Royal Institute of Technology.
    Gradient-Based Enhancement of Tubular Structures in Medical Images2015Inngår i: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 26, nr 1, s. 19-29Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Vesselness filters aim at enhancing tubular structures in medical images. The most popular vesselness filters are based on eigenanalyses of the Hessian matrix computed at different scales. However, Hessian-based methods have well-known limitations, most of them related to the use of second order derivatives. In this paper, we propose an alternative strategy in which ring-like patterns are sought in the local orientation distribution of the gradient. The method takes advantage of symmetry properties of ring-like patterns in the spherical harmonics domain. For bright vessels, gradients not pointing towards the center are filtered out from every local neighborhood in a first step. The opposite criterion is used for dark vessels. Afterwards, structuredness, evenness and uniformness measurements are computed from the power spectrum in spherical harmonics of both the original and the half-zeroed orientation distribution of the gradient. Finally, the features are combined into a single vesselness measurement. Alternatively, a structure tensor that is suitable for vesselness can be estimated before the analysis in spherical harmonics. The two proposed methods are called Ring Pattern Detector (RPD) and Filtered Structure Tensor (FST) respectively. Experimental results with computed tomography angiography data show that the proposed filters perform better compared to the state-of-the-art.

  • 26.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Smedby, Örjan
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Volume-Based Fabric Tensors through Lattice-Boltzmann Simulations2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper introduces a new methodology to compute fabric tensors from computational fluid dynamics simulations performed through the lattice-Boltzmann method. Trabecular bone is modeled as a pipeline where a synthetic viscous fluid can flow from a single source located at the center of a spherical region of interest toward its boundaries. Two fabric tensors are computed from local velocities at the steady state estimated from the simulations, a tortuosity and a normalized tortuosity tensor.The main advantage of the proposed fabric tensors is that, unlike previous approaches, they intentionally disregard the trabecular termini in the computations, which do not play an important role in the estimation of trabecular bone quality. Thus, the proposed fabric tensors are less prone than previously proposed ones to unnecessary reductions of anisotropy related to the the presence of trabecular termini. The results of experiments conducted on synthetic and micro-computed tomography data in 2D and 3D show the artificial fluid flowing inside the trabecular bone has negligible velocities at trabecular termini, reducing in that way their influence in the estimation of the proposed fabric tensors.

  • 27.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa. Linköpings universitet, Hälsouniversitetet.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Borga, Magnus
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    On the Efficiency of the Mean Intercept Length Tensor2011Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    The Mean Intercept Length tensor is one of the most used techniques to estimate microstructure orientation and anisotropy of materials from 2D or 3D binary images. This paper proposes an efficient implementation of this technique. First, the Extended Gaussian Image is computed for the binary image. Second, the intercepts are computed for all possible orientations through an angular convolution. Finally, the tensor is computed by means of the covariance matrix. The complexity of the method is O(n+m) in contrast with O(nm) of traditional implementations, where n is the number of voxels in the image and m is the number of orientations used in the computations.

  • 28.
    Moreno, Rodrigo
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Wang, Chunliang
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet.
    Smedby, Örjan
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Vessel Wall Segmentation Using Implicit Models and  Total Curvature Penalizers2013Inngår i: IMAGE ANALYSIS, SCIA 2013: 18TH SCANDINAVIAN CONFERENCE, Springer Berlin/Heidelberg, 2013, s. 299-308Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This book constitutes the refereed proceedings of the 18th Scandinavian Conference on Image Analysis, SCIA 2013, held in Espoo, Finland, in June 2013. The 67 revised full papers presented were carefully reviewed and selected from 132 submissions. The papers are organized in topical sections on feature extraction and segmentation, pattern recognition and machine learning, medical and biomedical image analysis, faces and gestures, object and scene recognition, matching, registration, and alignment, 3D vision, color and multispectral image analysis, motion analysis, systems and applications, human-centered computing, and video and multimedia analysis.

  • 29.
    Skoglund, Karin
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för läkemedelsforskning. Linköpings universitet, Hälsouniversitetet.
    Moreno, Samuel Boiso
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Jönsson, Jan-Ingvar
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för mikrobiologi och molekylär medicin. Linköpings universitet, Hälsouniversitetet.
    Vikingsson, Svante
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för läkemedelsforskning. Linköpings universitet, Hälsouniversitetet.
    Carlsson, Björn
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för läkemedelsforskning. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Klinisk farmakologi.
    Gréen, Henrik
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för läkemedelsforskning. Linköpings universitet, Hälsouniversitetet.
    Influence of variant ABCG2 on tyrosine kinase inhibitor transport and efficacy in the K562 chronic myeloid leukemia cell lineManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    Objective: The tyrosine kinase inhibitors (TKIs) used in the treatment of chronic myeloid leukemia are substrates for the efflux transport protein ABCG2. Variations in ABCG2 activity might influence pharmacokinetics and therapeutic outcome of TKIs. The role of ABCG2 single nucleotide polymorphisms (SNPs) in TKI treatment is not clear and functional in vitro studies are lacking. The aim of this study was to investigate the consequences of ABCG2 SNPs for transport and efficacy of TKIs (imatinib, N-desmethyl imatinib (CGP74588), dasatinib, nilotinib and bosutinib). Methods: ABCG2 SNPs 34G>A, 421C>A, 623T>C, 886G>C, 1574T>G and 1582G>A were constructed from ABCG2 wild type cDNA and transduced to K562 cells by retroviral gene transfer. The ability of variant cells to express ABCG2 in the cell membrane and protect against TKI cytotoxicity was investigated. Results: Wild type ABCG2 had a protective effect against the cytotoxicity of all investigated compounds except bosutinib. It was found that ABCG2 expression provided a better protection against CGP74588 than its parent compound, imatinib. ABCG2 421C>A, 623T>C, 886G>C and 1574T>G reduced cell membrane expression of ABCG2 and the protective effect of ABCG2 against imatinib, CGP74588, dasatinib and nilotinib cytotoxicity. The most prominent effect was found for the 623T>C SNP which resulted in undetectable ABCG2 expression and low protection against TKI cytotoxicity. Conclusion: These findings show that the ABCG2 SNPs 421C>A, 623T>C, 886G>C and 1574T>G impair ABCG2 transport function and might influence TKI pharmacokinetics in vivo. Furthermore, the active imatinib metabolite CGP74588 is to a greater extent than the parent compound transported by ABCG2.

  • 30.
    Wang, Chunliang
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Moreno, Rodrigo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Inter-project Cooperation Using Socket-Based Inter-Process Communication2012Konferansepaper (Annet vitenskapelig)
  • 31.
    Wang, Chunliang
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Moreno, Rodrigo
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Smedby, Örjan
    Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Hälsouniversitetet. Östergötlands Läns Landsting, Diagnostikcentrum, Röntgenkliniken i Linköping.
    Vessel Segmentation Using Implicit Model-Guided Level Sets2012Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper proposes an automatic segmentation method of vasculature that combines level-sets with an implicit 3D model of the vessels. First, a 3D vessel model from a set of initial centerlines is generated. This model is incorporated in the level set propagation to regulate the growth of the vessel contour. After evolving the level set, new centerlines are extracted and the diameter of vessels is re-estimated in order to generate a new vessel model. The propagation and re-modeling steps are repeated until convergence. The organizers of the 3D Cardiovascular Imaging: a MICCAI segmentation challenge report the following results for the 24 testing datasets. The sensitivity and PPV are 0.26, 0.40 for QCA and 0.05 and 0.22 for CTA. As for quantitation, the absolute and RMS dierences for QCA are 29.7% and 34.1% and the weighted kappa for CTA are -0.37. As for lumen segmentation, the dice are 0.68 and 0.69 for healthy and diseased vessel segments respectively. Performance for QCA and lumen segmentation are close to the reported by the organizers for three human observers.

1 - 31 of 31
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