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  • 501.
    Ynnerman, Anders
    et al.
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Norrkoping Visualizat Centre C, Sweden.
    Rydell, Thomas
    Interspectral AB, Sweden; Interact Institute Swedish ICT, Sweden.
    Antoine, Daniel
    British Museum, England; UCL, England.
    Hughes, David
    Interspectral AB, Sweden; Interact Institute Swedish ICT, Sweden.
    Persson, Anders
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ljung, Patric
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Norrkoping Visualizat Centre C, Sweden.
    Interactive Visualization of 3D Scanned Mummies at Public Venues2016In: Communications of the ACM, ISSN 0001-0782, E-ISSN 1557-7317, Vol. 59, no 12, p. 72-81Article in journal (Refereed)
    Abstract [en]

    BY COMBINING VISUALIZATION techniques with interactive multi-touch tables and intuitive user interfaces, visitors to museums and science centers can conduct self-guided tours of large volumetric image data. In an interactive learning experience, visitors become the explorers of otherwise invisible interiors of unique artifacts and subjects. Here, we take as our starting point the state of the art in scanning technologies, then discuss the latest research on high-quality interactive volume rendering and how it can be tailored to meet the specific demands

  • 502.
    Ynnerman, Anders
    et al.
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Rydell, Thomas
    Persson, Anders
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.
    Ernvik, Aron
    Forsell, Camilla
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
    Ljung, Patric
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
    Lundström, Claes
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Multi-Touch Table System for Medical Visualization2015In: Eurographics 2015: Dirk Bartz Prize, Eurographics - European Association for Computer Graphics, 2015Conference paper (Other academic)
    Abstract [en]

    Medical imaging plays a central role in a vast range of healthcare practices. While the usefulness of 3D visualizations is well known, the adoption of such technology has previously been limited in many medical areas. This paper, awarded the Dirk Bartz Prize for Visual Computing in Medicine 2015, describes the development of a medical multi-touch visualization table that successfully has reached its aim to bring 3D visualization to a wider clinical audience. The descriptions summarize the targeted clinical scenarios, the key characteristics of the system, and the user feedback obtained.

  • 503.
    Zaman, Shaikh Faisal
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Automated Liver Segmentation from MR-Images Using Neural Networks2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Liver segmentation is a cumbersome task when done manually, often consuming quality time of radiologists. Use of automation in such clinical task is fundamental and the subject of most modern research. Various computer aided methods have been incorporated for this task, but it has not given optimal results due to the various challenges faced as low-contrast in the images, abnormalities in the tissues, etc. As of present, there has been significant progress in machine learning and artificial intelligence (AI) in the field of medical image processing. Though challenges exist, like image sensitivity due to different scanners used to acquire images, difference in imaging methods used, just to name a few. The following research embodies a convolutional neural network (CNN) was incorporated for this process, specifically a U-net algorithm. Predicted masks are generated on the corresponding test data and the Dice similarity coefficient (DSC) is used as a statistical validation metric for performance evaluation. Three datasets, from different scanners (two1.5 T scanners and one 3.0 T scanner), have been evaluated. The U-net performs well on the given three different datasets, even though there was limited data for training, reaching upto DSC of 0.93 for one of the datasets.

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  • 504.
    Zech, Wolf-Dieter
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Institute of Forensic Medicine, University of Bern, Switzerland.
    Hottinger, Anna-Lena
    Institute of Forensic Medicine, University of Bern, Bern, Switzerland.
    Schwendener, Nicole
    Institute of Forensic Medicine, University of Bern, Bern, Switzerland.
    Schuster, Frederick
    Institute of Forensic Medicine, University of Bern, Bern, Switzerland; Department of Diagnostic, Interventional and Pediatric Radiology, University of Bern, Inselspital, Bern, Switzerland.
    Persson, Anders
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Warntjes, Marcel Jan Bertus
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Jackowski, Christian
    Institute of Forensic Medicine, University of Bern, Bern, Switzerland.
    Post-mortem 1.5T MR quantification of regular anatomical brain structures2016In: International journal of legal medicine (Print), ISSN 0937-9827, E-ISSN 1437-1596, Vol. 130, no 4, p. 1071-1080Article in journal (Refereed)
    Abstract [en]

    Recently, post-mortem MR quantification has been introduced to the field of post-mortem magnetic resonance imaging. By usage of a particular MR quantification sequence, T1 and T2 relaxation times and proton density (PD) of tissues and organs can be quantified simultaneously. The aim of the present basic research study was to assess the quantitative T1, T2, and PD values of regular anatomical brain structures for a 1.5T application and to correlate the assessed values with corpse temperatures. In a prospective study, 30 forensic cases were MR-scanned with a quantification sequence prior to autopsy. Body temperature was assessed during MR scans. In synthetically calculated T1, T2, and PD-weighted images, quantitative T1, T2 (both in ms) and PD (in %) values of anatomical structures of cerebrum (Group 1: frontal gray matter, frontal white matter, thalamus, internal capsule, caudate nucleus, putamen, and globus pallidus) and brainstem/cerebellum (Group 2: cerebral crus, substantia nigra, red nucleus, pons, cerebellar hemisphere, and superior cerebellar peduncle) were assessed. The investigated brain structures of cerebrum and brainstem/cerebellum could be characterized and differentiated based on a combination of their quantitative T1, T2, and PD values. MANOVA testing verified significant differences between the investigated anatomical brain structures among each other in Group 1 and Group 2 based on their quantitative values. Temperature dependence was observed mainly for T1 values, which were slightly increasing with rising temperature in the investigated brain structures in both groups. The results provide a base for future computer-aided diagnosis of brain pathologies and lesions in post-mortem magnetic resonance imaging.

  • 505.
    Zech, Wolf-Dieter
    et al.
    Institute of Forensic Medicine University of Bern Switzerland.
    Schwendener, Nicole
    Institute of Forensic Medicine University of Bern Switzerland.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Bertus Warntjes, Marcel, Jan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Jackowski, Christian
    Institute of Forensic Medicine University of Bern Switzerland.
    Temperature dependence of postmortem MR quantification for soft tissue discrimination2015In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Temperature dependence of postmortem MR quantification for soft tissue discrimination, Vol. 25, no 8, p. 2381-2389Article in journal (Refereed)
    Abstract [en]

    Objectives To investigate and correct the temperature dependence of postmortem MR quantification used for soft tissue characterization and differentiation in thoraco-abdominal organs. Material and methods Thirty-five postmortem short axis cardiac 3-T MR examinations were quantified using a quantification sequence. Liver, spleen, left ventricular myocardium, pectoralis muscle and subcutaneous fat were analysed in cardiac short axis images to obtain mean T1, T2 and PD tissue values. The core body temperature was measured using a rectally inserted thermometer. The tissue-specific quantitative values were related to the body core temperature. Equations to correct for temperature differences were generated. Results In a 3D plot comprising the combined data of T1, T2 and PD, different organs/tissues could be well differentiated from each other. The quantitative values were influenced by the temperature. T1 in particular exhibited strong temperature dependence. The correction of quantitative values to a temperature of 37 °C resulted in better tissue discrimination. Conclusion Postmortem MR quantification is feasible for soft tissue discrimination and characterization of thoracoabdominal organs. This provides a base for computer-aided diagnosis and detection of tissue lesions. The temperature dependence of the T1 values challenges postmortem MR quantification. Equations to correct for the temperature dependence are provided.

  • 506.
    Zech, Wolf-Dieter
    et al.
    University of Bern, Switzerland.
    Schwendener, Nicole
    University of Bern, Switzerland.
    Persson, Anders
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Warntjes, Marcel Jan Bertus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Jackowski, Christian
    University of Bern, Switzerland.
    Postmortem MR quantification of the heart for characterization and differentiation of ischaemic myocardial lesions2015In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 25, no 7, p. 2067-2073Article in journal (Refereed)
    Abstract [en]

    Recently, an MRI quantification sequence has been developed which can be used to acquire T1- and T2-relaxation times as well as proton density (PD) values. Those three quantitative values can be used to describe soft tissue in an objective manner. The purpose of this study was to investigate the applicability of quantitative cardiac MRI for characterization and differentiation of ischaemic myocardial lesions of different age. Fifty post-mortem short axis cardiac 3 T MR examinations have been quantified using a quantification sequence. Myocardial lesions were identified according to histology and appearance in MRI images. Ischaemic lesions were assessed for mean T1-, T2- and proton density values. Quantitative values were plotted in a 3D-coordinate system to investigate the clustering of ischaemic myocardial lesions. A total of 16 myocardial lesions detected in MRI images were histologically characterized as acute lesions (n = 8) with perifocal oedema (n = 8), subacute lesions (n = 6) and chronic lesions (n = 2). In a 3D plot comprising the combined quantitative values of T1, T2 and PD, the clusters of all investigated lesions could be well differentiated from each other. Post-mortem quantitative cardiac MRI is feasible for characterization and discrimination of different age stages of myocardial infarction. aEuro cent MR quantification is feasible for characterization of different stages of myocardial infarction. aEuro cent The results provide the base for computer-aided MRI cardiac infarction diagnosis. aEuro cent Diagnostic criteria may also be applied for living patients.

  • 507.
    Zech, Wolf-Dieter
    et al.
    University of Bern, Switzerland.
    Schwendener, Nicole
    University of Bern, Switzerland.
    Persson, Anders
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Warntjes, Marcel Jan Bertus
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Riva, Fabiano
    University of Bern, Switzerland.
    Schuster, Frederick
    University of Bern, Switzerland; Hospital and University of Bern, Switzerland.
    Jackowski, Christian
    University of Bern, Switzerland.
    Postmortem quantitative 1.5-T MRI for the differentiation and characterization of serous fluids, blood, CSF, and putrefied CSF2015In: International journal of legal medicine (Print), ISSN 0937-9827, E-ISSN 1437-1596, Vol. 129, no 5, p. 1127-1136Article in journal (Refereed)
    Abstract [en]

    The purpose of the present study was to investigate whether serous fluids, blood, cerebrospinal fluid (CSF), and putrefied CSF can be characterized and differentiated in synthetically calculated magnetic resonance (MR) images based on their quantitative T (1), T (2), and proton density (PD) values. Images from 55 postmortem short axis cardiac and 31 axial brain 1.5-T MR examinations were quantified using a quantification sequence. Serous fluids, fluid blood, sedimented blood, blood clots, CSF, and putrefied CSF were analyzed for their mean T (1), T (2), and PD values. Body core temperature was measured during the MRI scans. The fluid-specific quantitative values were related to the body core temperature. Equations to correct for temperature differences were generated. In a 3D plot as well as in statistical analysis, the quantitative T (1), T (2) and PD values of serous fluids, fluid blood, sedimented blood, blood clots, CSF, and putrefied CSF could be well differentiated from each other. The quantitative T (1) and T (2) values were temperature-dependent. Correction of quantitative values to a temperature of 37 A degrees C resulted in significantly better discrimination between all investigated fluid mediums. We conclude that postmortem 1.5-T MR quantification is feasible to discriminate between blood, serous fluids, CSF, and putrefied CSF. This finding provides a basis for the computer-aided diagnosis and detection of fluids and hemorrhages.

  • 508.
    Zinner, Christoph
    et al.
    University of Wurzburg, Germany; Mid Sweden University, Sweden.
    Morales-Alamo, David
    University of Las Palmas Gran Canaria, Spain; University of Las Palmas Gran Canaria, Spain.
    Ortenblad, Niels
    Mid Sweden University, Sweden; University of Southern Denmark, Denmark.
    Larsen, Filip J.
    Swedish School Sport and Health Science, Sweden.
    Schiffer, Tomas
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Willis, Sarah J.
    Mid Sweden University, Sweden.
    Gelabert-Rebato, Miriam
    University of Las Palmas Gran Canaria, Spain; University of Las Palmas Gran Canaria, Spain.
    Perez-Valera, Mario
    University of Las Palmas Gran Canaria, Spain; University of Las Palmas Gran Canaria, Spain.
    Boushel, Robert
    University of British Columbia, Canada.
    Calbet, Jose A. L.
    University of Las Palmas Gran Canaria, Spain; University of Las Palmas Gran Canaria, Spain; University of British Columbia, Canada.
    Holmberg, Hans-Christer
    Mid Sweden University, Sweden; University of British Columbia, Canada; UiT Arctic University of Norway, Norway.
    The Physiological Mechanisms of Performance Enhancement with Sprint Interval Training Differ between the Upper and Lower Extremities in Humans2016In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 7, no 426Article in journal (Refereed)
    Abstract [en]

    To elucidate the mechanisms underlying the differences in adaptation of arm and leg muscles to sprint training, over a period of 11 days 16 untrained men performed six sessions of 4-6 x 30-s all-out sprints (SIT) with the legs and arms, separately, with a 1-h interval of recovery. Limb-specific VO(2)peak, sprint performance (two 30-s Wingate tests with 4-min recovery), muscle efficiency and time-trial performance (TT, 5-min all-out) were assessed and biopsies from the m. vastus lateralis and m. triceps brachii taken before and after training. VO(2)peak and Wmax increased 3-11% after training, with a more pronounced change in the arms (P amp;lt; 0.05). Gross efficiency improved for the arms (+8.8%, P amp;lt; 0.05), but not the legs (-0.6%). Wingate peak and mean power outputs improved similarly for the arms and legs, as did TT performance. After training, VO2 during the two Wingate tests was increased by 52 and 6% for the arms and legs, respectively (P amp;lt; 0.001). In the case of the arms, VO2 was higher during the first than second Wingate test (64 vs. 44%, P amp;lt; 0.05). During the TT, relative exercise intensity, HR, VO2, VCO2, V-E, and V-t were all lower during arm-cranking than leg-pedaling, and oxidation of fat was minimal, remaining so after training. Despite the higher relative intensity, fat oxidation was 70% greater during leg-pedaling (P = 0.017). The aerobic energy contribution in the legs was larger than for the arms during the Wingate tests, although VO2 for the arms was enhanced more by training, reducing the O-2 deficit after SIT. The levels of muscle glycogen, as well as the myosin heavy chain composition were unchanged in both cases, while the activities of 3-hydroxyacyl-CoA-dehydrogenase and citrate synthase were elevated only in the legs and capillarization enhanced in both limbs. Multiple regression analysis demonstrated that the variables that predict TT performance differ for the arms and legs. The primary mechanism of adaptation to SIT by both the arms and legs is enhancement of aerobic energy production. However, with their higher proportion of fast muscle fibers, the arms exhibit greater plasticity.

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  • 509.
    Ödén, Jakob
    et al.
    Stockholm University and RaySearch Laboratories AB, Stockholm, Sweden.
    Toma-Dasu, Iuliana
    Stockholm University and Karolinska Institutet, Stockholm, Sweden.
    Eriksson, Kjell
    RaySearch Laboratories AB, Stockholm, Sweden.
    Flejmer, Anna M.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Oncology.
    Dasu, Alexandru
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. The Skandion Clinic, Uppsala, Sweden.
    The influence of breathing motion and a variable relative biological effectiveness in proton therapy of left-sided breast cancer2017In: Acta Oncologica, ISSN 0284-186X, E-ISSN 1651-226X, Vol. 56, no 11, p. 1428-1436Article in journal (Refereed)
    Abstract [en]

    Background: Proton breast radiotherapy has been suggested to improve target coverage as well as reduce cardiopulmonary and integral dose compared with photon therapy. This study aims to assess this potential when accounting for breathing motion and a variable relative biological effectiveness (RBE).

    Methods: Photon and robustly optimized proton plans were generated to deliver 50 Gy (RBE) in 25 fractions (RBE=1.1) to the CTV (whole left breast) for 12 patients. The plan evaluation was performed using the constant RBE and a variable RBE model. Robustness against breathing motion, setup, range and RBE uncertainties was analyzed using CT data obtained at free-breathing, breath-hold-at-inhalation and breath-hold-at-exhalation.

    Results: All photon and proton plans (RBE=1.1) met the clinical goals. The variable RBE model predicted an average RBE of 1.18 for the CTVs (range 1.14–1.21) and even higher RBEs in organs at risk (OARs). However, the dosimetric impact of this latter aspect was minor due to low OAR doses. The normal tissue complication probability (NTCP) for the lungs was low for all patients (<1%), and similar for photons and protons. The proton plans were generally considered robust for all patients. However, in the most extreme scenarios, the lowest dose received by 98% of the CTV dropped from 96 to 99% of the prescribed dose to around 92–94% for both protons and photons. Including RBE uncertainties in the robustness analysis resulted in substantially higher worst-case OAR doses.

    Conclusions: Breathing motion seems to have a minor effect on the plan quality for breast cancer. The variable RBE might impact the potential benefit of protons, but could probably be neglected in most cases where the physical OAR doses are low. However, to be able to identify outlier cases at risk for high OAR doses, the biological evaluation of proton plans taking into account the variable RBE is recommended.

  • 510.
    Örtenberg, Alexander
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
    Magnusson, Maria
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering. Linköping University, Faculty of Medicine and Health Sciences.
    Sandborg, Michael
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Alm Carlsson, Gudrun
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Malusek, Alexandr
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    PARALLELISATION OF THE MODEL-BASED ITERATIVE RECONSTRUCTION ALGORITHM DIRA2016In: Radiation Protection Dosimetry, ISSN 0144-8420, E-ISSN 1742-3406, Vol. 169, no 1-4, p. 405-409Article in journal (Refereed)
    Abstract [en]

    New paradigms for parallel programming have been devised to simplify software development on multi-core processors and many-core graphical processing units (GPU). Despite their obvious benefits, the parallelisation of existing computer programs is not an easy task. In this work, the use of the Open Multiprocessing (OpenMP) and Open Computing Language (OpenCL) frameworks is considered for the parallelisation of the model-based iterative reconstruction algorithm DIRA with the aim to significantly shorten the code’s execution time. Selected routines were parallelised using OpenMP and OpenCL libraries; some routines were converted from MATLAB to C and optimised. Parallelisation of the code with the OpenMP was easy and resulted in an overall speedup of 15 on a 16-core computer. Parallelisation with OpenCL was more difficult owing to differences between the central processing unit and GPU architectures. The resulting speedup was substantially lower than the theoretical peak performance of the GPU; the cause was explained.

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  • 511.
    Persson, Anders (Contributor)
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences.
    Strategic research agenda for biomedical imaging2019In: Insights into Imaging, no 10, article id 7Article in journal (Refereed)
    Abstract [en]

    This Strategic Research Agenda identifies current challenges and needs in healthcare, illustrates how biomedical imaging and derived data can help to address these, and aims to stimulate dedicated research funding efforts.

    Medicine is currently moving towards a more tailored, patient-centric approach by providing personalised solutions for the individual patient. Innovation in biomedical imaging plays a key role in this process as it addresses the current needs for individualised prevention, treatment, therapy response monitoring, and image-guided surgery.

    The use of non-invasive biomarkers facilitates better therapy prediction and monitoring, leading to improved patient outcomes. Innovative diagnostic imaging technologies provide information about disease characteristics which, coupled with biological, genetic and -omics data, will contribute to an individualised diagnosis and therapy approach.

    In the emerging field of theranostics, imaging tools together with therapeutic agents enable the selection of best treatments and allow tailored therapeutic interventions.

    For prenatal monitoring, the use of innovative imaging technologies can ensure an early detection of malfunctions or disease.

    The application of biomedical imaging for diagnosis and management of lifestyle-induced diseases will help to avoid disease development through lifestyle changes.

    Artificial intelligence and machine learning in imaging will facilitate the improvement of image interpretation and lead to better disease prediction and therapy planning.

    As biomedical imaging technologies and analysis of existing imaging data provide solutions to current challenges and needs in healthcare, appropriate funding for dedicated research is needed to implement the innovative approaches for the wellbeing of citizens and patients.

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