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Pettersson, Johanna
Publications (10 of 16) Show all publications
Pettersson, J., Palmerius, K., Knutsson, H., Wahlström, O., Tillander, B. & Borga, M. (2008). Simulation of Patient Specific Cervical Hip Fracture Surgery With a Volume Haptic Interface. IEEE Transactions on Biomedical Engineering, 55(4), 1255-1265
Open this publication in new window or tab >>Simulation of Patient Specific Cervical Hip Fracture Surgery With a Volume Haptic Interface
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2008 (English)In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 55, no 4, p. 1255-1265Article in journal (Refereed) Published
Abstract [en]

The interest for surgery simulator systems with anatomical models generated from authentic patient data is growing as these systems evolve.With access to volumetric patient data, e.g., from a computer tomography scan, haptic and visual feedback can be created directly from this dataset. This opens the door for patient specific simulations. Hip fracture surgery is one area where simulator systems is useful to train new surgeons and plan operations. To simulate the drilling procedure in this type of surgery, a repositioning of the fractured bone into correct position is first needed. This requires a segmentation process in which the bone segments are identified and the position of the dislocated part is determined. The segmentation must be automatic to cope with the large amount of data from the computer tomography scan. This work presents the first steps in the development of a hip fracture surgery simulation with patient specific models. Visual and haptic feedback is generated from the computer tomography data by simulating fluoroscopic images and the drilling process. We also present an automatic segmentation method to identify the fractured bone and determine the dislocation. This segmentation method is based on nonrigid registration with the Morphon method.

Place, publisher, year, edition, pages
IEEE, 2008
Keywords
Automatic segmentation, patient specific data, registration, surgery simulation, volume haptics.
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-19648 (URN)10.1109/TBME.2007.908099 (DOI)000254219900001 ()
Available from: 2009-07-09 Created: 2009-07-09 Last updated: 2017-12-13
Rodríguez-Vila, B., Pettersson, J., Borga, M., García-Vicente, F., Gómez, E. J. & Knutsson, H. (2007). 3D deformable registration for monitoring radiotherapy treatment in prostate cancer. In: Ersboll, BK; Pedersen, KS (Ed.), Image Analysis: 15th Scandinavian Conference, SCIA 2007, Aalborg, Denmark, June 10-14, 2007. Paper presented at 15th Scandinavian Conference, SCIA 2007, Aalborg, Denmark, June 10-14, 2007 (pp. 750-759). Berlin/Heidelberg, Germany: Springer Berlin/Heidelberg
Open this publication in new window or tab >>3D deformable registration for monitoring radiotherapy treatment in prostate cancer
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2007 (English)In: Image Analysis: 15th Scandinavian Conference, SCIA 2007, Aalborg, Denmark, June 10-14, 2007, Berlin/Heidelberg, Germany: Springer Berlin/Heidelberg, 2007, p. 750-759Conference paper, Published paper (Refereed)
Abstract [en]

Two deformable registration methods, the Demons and the Morphon algorithms, have been used for registration of CT datasets to evaluate their usability in radiotherapy planning for prostate cancer. These methods were chosen because they can perform deformable registration in a fully automated way. The experiments show that for intrapatient registration both of the methods give useful results, although some differences exist in the way they deform the template. The Morphon method has, however, some advantageous compared to the Demons method. It is invariant to the image intensity and it does not distort the deformed data. The conclusion is therefore to recommend the Morphon method as a registration tool for this application. A more flexible regularization model is needed, though, in order to be able to catch the full range of deformations required to match the datasets.

Place, publisher, year, edition, pages
Berlin/Heidelberg, Germany: Springer Berlin/Heidelberg, 2007
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 4522
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-38281 (URN)10.1007/978-3-540-73040-8_76 (DOI)000247364000076 ()43425 (Local ID)978-3-540-73039-2 (ISBN)3540730400 (ISBN)978-3-540-73040-8 (ISBN)43425 (Archive number)43425 (OAI)
Conference
15th Scandinavian Conference, SCIA 2007, Aalborg, Denmark, June 10-14, 2007
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2018-02-06Bibliographically approved
Parraga, A., Pettersson, J., Susin, A., De Craene, M. & Marq, B. (2007). Non-rigid registration methods assessment of 3D CT images for head-neck radiotherapy. In: Josien P. W. Pluim; Joseph M. Reinhardt (Ed.), Medical Imaging 2007: Image Processing. Paper presented at Medical Imaging 2007: Image Processing, 17 February 2007, San Diego, CA, USA (pp. 6512H1-6512H9). SPIE - International Society for Optical Engineering
Open this publication in new window or tab >>Non-rigid registration methods assessment of 3D CT images for head-neck radiotherapy
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2007 (English)In: Medical Imaging 2007: Image Processing / [ed] Josien P. W. Pluim; Joseph M. Reinhardt, SPIE - International Society for Optical Engineering, 2007, p. 6512H1-6512H9Conference paper, Published paper (Other academic)
Abstract [en]

Intensity Modulated Radiotherapy is a new technique enabling the sculpting of the 3D radiation dose. It enables to modulate the delivery of the dose inside the malignant areas and constrain the radiation plan for protecting important functional areas. It also raises the issues of adequacy and accuracy of the selection and delineation of the target volumes. The delineation in the patient image of the tumor volume is highly time-consuming and requires considerable expertise. In this paper we focus on atlas based automatic segmentation of head and neck patients and compare two non-rigid registration methods: B-Spline and Morphons. To assess the quality of each method, we took a set of four 3D CT patient's images previously segmented by a doctor with the organs at risk. After a preliminary affine registration, both non-rigid registration algorithms were applied to match the patient and atlas images. Each deformation field, resulted from the non-rigid deformation, was applied on the masks corresponding to segmented regions in the atlas. The atlas based segmentation masks were compared to manual segmentations performed by an expert. We conclude that Morphons has performed better for matching all structures being considered, improving in average 11% the segmentation.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2007
Series
Proceedings of SPIE (Progress in biomedical optics and imaging), ISSN 1605-7422 ; 6512
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-38751 (URN)10.1117/12.709368 (DOI)000246288500052 ()45483 (Local ID)9780819466303 (ISBN)45483 (Archive number)45483 (OAI)
Conference
Medical Imaging 2007: Image Processing, 17 February 2007, San Diego, CA, USA
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2014-01-31
Rydell, J., Knutsson, H., Pettersson, J., Johansson, A., Farnebäck, G., Dahlqvist Leinhard, O., . . . Borga, M. (2007). Phase Sensitive Reconstruction for Water/Fat Separation in MR Imaging Using Inverse Gradient. In: Nicholas Ayache, Sébastien Ourselin, Anthony Maeder (Ed.), Nicholas Ayache, Sebastien Ourselin and Anthony Maeder (Ed.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part I: . Paper presented at MICCAI 2007, The 10th International Conference on Medical Image Computing and Computer Assisted Interventio, October 29-November 2, Brisbane, Australia (pp. 210-218). Springer Berlin/Heidelberg
Open this publication in new window or tab >>Phase Sensitive Reconstruction for Water/Fat Separation in MR Imaging Using Inverse Gradient
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2007 (English)In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part I / [ed] Nicholas Ayache, Sebastien Ourselin and Anthony Maeder, Springer Berlin/Heidelberg, 2007, p. 210-218Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a novel method for phase unwrapping for phase sensitive reconstruction in MR imaging. The unwrapped phase is obtained by integrating the phase gradient by solving a Poisson equation. An efficient solver, which has been made publicly available, is used to solve the equation. The proposed method is demonstrated on a fat quantification MRI task that is a part of a prospective study of fat accumulation. The method is compared to a phase unwrapping method based on region growing. Results indicate that the proposed method provides more robust unwrapping. Unlike region growing methods, the proposed method is also straight-forward to implement in 3D.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2007
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 4791
Keywords
MRI
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12661 (URN)10.1007/978-3-540-75757-3_26 (DOI)000250916000026 ()978-3-540-75756-6 (ISBN)978-3-540-75757-3 (ISBN)
Conference
MICCAI 2007, The 10th International Conference on Medical Image Computing and Computer Assisted Interventio, October 29-November 2, Brisbane, Australia
Available from: 2007-11-07 Created: 2007-11-07 Last updated: 2019-06-14
Parraga, A., Susin, A., Pettersson, J., Marq, B. & De Craene, M. (2007). Quality Assessment of Non-rigid Registration Methods for Atlas-based Segmentation in Head-neck Radiotherapy. In: ICASSP 2007. Paper presented at IEEE International Conference on Acoustics, Speech and Signal Processing, Honolulu, HI, USA; 15-20 April 2007 (pp. I-445-I-448). IEEE
Open this publication in new window or tab >>Quality Assessment of Non-rigid Registration Methods for Atlas-based Segmentation in Head-neck Radiotherapy
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2007 (English)In: ICASSP 2007, IEEE , 2007, p. I-445-I-448Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we compare three non-rigid registration methods for atlas-based segmentation: B-splines, morphons and a combination of morphons and demons. To assess the quality of each method, we use a data set of four patients, containing for each patient the computed tomography (CT) image and a manual segmentation of the organs at risk performed by an expert of the head and neck anatomy. Non-rigid registration algorithms have been used to match the patient and atlas images. Each deformation field, resulting from the non-rigid deformation, have been applied on the masks corresponding to segmented regions in the atlas. The atlas based segmented masks have been compared to manual segmentations performed by the expert. The results show that the combined method (morphons + demons) achieves the best performances on this dataset resulting in an average improvement of 6% with respect to morphons and 18% with respect to B-spline.

Place, publisher, year, edition, pages
IEEE, 2007
Series
IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings, ISSN 1520-6149 ; Vol. 1
Keywords
biomedical imaging processing, image registration, image segmentation
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-38750 (URN)10.1109/ICASSP.2007.366712 (DOI)45482 (Local ID)1-4244-0727-3 (ISBN)45482 (Archive number)45482 (OAI)
Conference
IEEE International Conference on Acoustics, Speech and Signal Processing, Honolulu, HI, USA; 15-20 April 2007
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2012-09-20Bibliographically approved
Pettersson, J., Knutsson, H. & Borga, M. (2007). Segmentation and registration with the Morphon method, four different applications. In: Proceedings of the {SSBA} Symposium on Image Analysis,2007: . Paper presented at Swedish Symposium in Image Analysis 2007 (SSBA), Linköping, Sweden,14-15 March 2007.
Open this publication in new window or tab >>Segmentation and registration with the Morphon method, four different applications
2007 (English)In: Proceedings of the {SSBA} Symposium on Image Analysis,2007, 2007Conference paper, Published paper (Other academic)
Abstract [en]

The Morphon method has shown to be a useful non-rigid registration method since it was first presented in 2005. This paper demonstrates how the method has been adapted for four different applications; hip fracture segmentation from CT data, hippocampus segmentation from MR data and registration the prostate and the head-neck region from CT data for radiotherapy planning.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-38744 (URN)45474 (Local ID)45474 (Archive number)45474 (OAI)
Conference
Swedish Symposium in Image Analysis 2007 (SSBA), Linköping, Sweden,14-15 March 2007
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2014-10-08
Pettersson, J., Knutsson, H., Nordqvist, P. & Borga, M. (2006). A hip surgery simulator based on patient specific models generated by automatic segmentation. In: James D Westwood; et al (Ed.), James D Westwood; et al (Ed.), Medicine Meets Virtual Reality 14: Accelerating Change in Healthcare: Next Medical Toolkit. Paper presented at Medicine Meets Virtual Reality Conference MMVR06,2006 (pp. 431-436). Amsterdam, Nederländerna: IOS Press
Open this publication in new window or tab >>A hip surgery simulator based on patient specific models generated by automatic segmentation
2006 (English)In: Medicine Meets Virtual Reality 14: Accelerating Change in Healthcare: Next Medical Toolkit / [ed] James D Westwood; et al, Amsterdam, Nederländerna: IOS Press, 2006, p. 431-436Conference paper, Published paper (Refereed)
Abstract [en]

The use of surgical simulator systems for education and preoperative planning is likely to increase in the future. A natural course of development of these systems is to incorporate patient specific anatomical models. This step requires some kind of segmentation process in which the different anatomical parts are extracted. Anatomical datasets are, however, usually very large and manual processing would be too demanding. Hence, automatic, or semi-automatic, methods to handle this step are required. The framework presented in this paper uses nonrigid registration, based on the morphon method, to automatically segment the hip anatomy and generate models for a hip surgery simulator system.

Place, publisher, year, edition, pages
Amsterdam, Nederländerna: IOS Press, 2006
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 119
Keywords
Surgery simulation, hip, patient specific models, segmentation, registration, morphon
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-32716 (URN)000269690200092 ()18638 (Local ID)978-1-58603-583-9 (ISBN)18638 (Archive number)18638 (OAI)
Conference
Medicine Meets Virtual Reality Conference MMVR06,2006
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2015-10-08Bibliographically approved
Pettersson, J. (2006). Automatic generation of patient specific models for hip surgery simulation. (Licentiate dissertation). Linköping: Linköpings universitet
Open this publication in new window or tab >>Automatic generation of patient specific models for hip surgery simulation
2006 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Simulation of surgical procedures in computer based simulator systems is a relatively new area of interest in the field of medical technology. Many different systems are under development, but it is still far until this technique becomes routine in a clinical environment.

One limitation with these systems is that the computer generated models of the anatomy are ususally not patient specific. In general these systems contain one or a couple of generic models, reflecting the normal anatomy. In order to use these systems as tools for preoperative planning, it must be possible to generate computer models from real patient cases. This is relevant also when these systems are used for training and education, since the surgeon can practice on a variety of real cases, ranging from routine procedures to more complex, or more unusual, tasks.

To produce patient specific models a segmentation process is generally involved. A manual segmentation method, where a user delineates the interesting structure slice by slice in a patient dataset, is a very tedious process, and the result tends to vary between different users. The results would be more consistent, and the process would be more time and cost efficient, if a computer performed this task automatically, with a limited amount of user interaction.

This work focus on automatic segmentation of hip bones from computer tomography scans, in order to generate patient specific computer models for a hip fracture surgery simulator. The segmentation is carried out by matching a template dataset to a patient dataset using a method called the morphon method. Each point in the template is categorised as one of three tissue types, soft tissue (background), spongy bone (bone interior), or cortical bone (bone surface). When this dataset has been matched to the patient dataset the information in the template can be projected onto the patient dataset and used to find the different objects in this dataset.

The presented method can be used in other applications as well. One example demonstrated in this thesis is segmentation of a structure in the brain called the hippocampus.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet, 2006. p. 49
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1243
Series
LiU-TEK-LIC ; 24
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-34135 (URN)20909 (Local ID)91-85523-95-X (ISBN)20909 (Archive number)20909 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-11-26
Pettersson, J., Knutsson, H. & Borga, M. (2006). Automatic hip bone segmentation using non-rigid registration. In: 18th International Conference on Pattern Recognition, 2006, ICPR 2006 (Volume:3 ): . Paper presented at 18th International Conference on Pattern Recognition, (ICPR 2006), 20-24 August 2006, Hong Kong (pp. 946-949). IEEE Computer Society
Open this publication in new window or tab >>Automatic hip bone segmentation using non-rigid registration
2006 (English)In: 18th International Conference on Pattern Recognition, 2006, ICPR 2006 (Volume:3 ), IEEE Computer Society, 2006, p. 946-949Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a method for automatic segmentation of bone from volumetric computed tomography (CT) data. Due to osteoporosis, which degenerates the bone density and hence decreases the intensity of the bone in the CT dataset, it is not possible to use conventional thresholding techniques to handle the segmentation. Furthermore we want to use prior knowledge about shapes and relations of the bones in the area of interest to be able to e.g. separate adjoining bones from each other. The method we suggest is the morphon algorithm in Knutsson and Andersson (2005). This is a non-rigid registration technique where an 2D or 3D image is iteratively deformed to match the corresponding structure in a target image. The method uses difference in local quadrature phase and certainty measures to estimate the deformations

Place, publisher, year, edition, pages
IEEE Computer Society, 2006
Series
International Conference on Pattern Recognition, ISSN 1051-4651
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-34138 (URN)10.1109/ICPR.2006.299 (DOI)000240705600228 ()20912 (Local ID)0-7695-2521-0 (ISBN)20912 (Archive number)20912 (OAI)
Conference
18th International Conference on Pattern Recognition, (ICPR 2006), 20-24 August 2006, Hong Kong
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2015-10-09Bibliographically approved
Pettersson, J., Knutsson, H. & Borga, M. (2006). Non-rigid registration for automatic fracture segmentation. In: Image Processing, 2006: . Paper presented at IEEE International Conference on Image Processing (ISIP 2006), 8-11 October 2006, Atlanta, GA, USA (pp. 1185-1188). Atlanta: IEEE
Open this publication in new window or tab >>Non-rigid registration for automatic fracture segmentation
2006 (English)In: Image Processing, 2006, Atlanta: IEEE , 2006, p. 1185-1188Conference paper, Published paper (Refereed)
Abstract [en]

Automatic segmentation of anatomical structures is often performed using model-based non-rigid registration methods. These algorithms work well when the images do not contain any large deviations from the normal anatomy. We have previously used such a method to generate patient specific models of hip bones for surgery simulation. The method that was used, the morphon method, registers two-or three-dimensional images using a multi-resolution deformation scheme. A prototype image is iteratively registered to a target image using quadrature filter phase difference to estimate the local displacement. The morphon method has in this work been extended to deal with automatic segmentation of fractured bones. Two features have been added. First, the method is modified such that multiple prototypes (in this case two) can be used. Second, normalised convolution is utilized for the displacement estimation, to guide the registration of the second prototype, based on the result of the registration of the first one

Place, publisher, year, edition, pages
Atlanta: IEEE, 2006
Series
International Conference on Image Processing. Proceedings, ISSN 1522-4880
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-34136 (URN)10.1109/ICIP.2006.312695 (DOI)000245768500297 ()20910 (Local ID)1-4244-0480-0 (ISBN)e-1-4244-0481-9 (ISBN)20910 (Archive number)20910 (OAI)
Conference
IEEE International Conference on Image Processing (ISIP 2006), 8-11 October 2006, Atlanta, GA, USA
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2015-10-09
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