| 1. |
- Pettersson, Johanna, 1977-, et al.
(författare)
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A hip surgery simulator based on patient specific models generated by automatic segmentation
- 2006
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Ingår i: Medicine Meets Virtual Reality 14: Accelerating Change in Healthcare. - Amsterdam, Nederländerna : IOS Press. - 9781586035839 ; , s. 431-436
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 2. |
- Pettersson, Johanna, 1977-, et al.
(författare)
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Automatic hip bone segmentation using non-rigid registration
- 2006
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Ingår i: 18th International Conference on Pattern Recognition, 2006, ICPR 2006 (Volume:3 ). - : IEEE Computer Society. - 0769525210 ; , s. 946-949
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Konferensbidrag (refereegranskat)abstract
- 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
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| 3. |
- Pettersson, Johanna, 1977-, et al.
(författare)
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Generation of patient specific bone models from volume data using morphons
- 2005
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Ingår i: IFMBE Proceedings. - Umeå : IFMBE. ; , s. 199-200
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Konferensbidrag (refereegranskat)abstract
- The use of simulator systems for surgical planning and training is growing as the systems become more advanced. One important feature of these systems is the possibility to work on real patient data. This paper presents a method for generating patient-specific models of the femoral bone and the pelvis to be used in a hip surgery simulator. The bones are segmented from volumetric CT data using the Morphon method [3], where a prototype pattern is iteratively morphed to fit the corresponding structure in the input data.
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| 4. |
- Pettersson, Johanna, 1977-, et al.
(författare)
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Non-rigid registration for automatic fracture segmentation
- 2006
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Ingår i: Image Processing, 2006. - Atlanta : IEEE. - 1424404800 ; , s. 1185-1188
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Konferensbidrag (refereegranskat)abstract
- 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
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| 5. |
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| 6. |
- Pettersson, Johanna, 1977-, et al.
(författare)
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Segmentation and registration with the Morphon method, four different applications
- 2007
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Ingår i: Proceedings of the {SSBA} Symposium on Image Analysis,2007.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 7. |
- Pettersson, Johanna, 1977-, et al.
(författare)
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Some issues on the segmentation of the femur in CT data
- 2004
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Ingår i: Proceedings of the Swedish Symposium on Image Analysis (2004). ; , s. 158-161
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This paper presents a recently started project which goal is to automatically generate patient specific models for visual and haptic simulation of hip fracture surgery. It includes a preliminary study of a computed tomography (CT) dataset of the pelvic region. The paper emphasizes some issues encountered when segmenting bones in this region, especially in the area around the proximal femur.
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| 8. |
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| 9. |
- Rodríguez-Vila, Borja, et al.
(författare)
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3D deformable registration for monitoring radiotherapy treatment in prostate cancer
- 2007
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Ingår i: Image Analysis. - Berlin/Heidelberg, Germany : Springer Berlin/Heidelberg. - 9783540730392 - 3540730400 - 9783540730408 ; , s. 750-759
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Konferensbidrag (refereegranskat)abstract
- 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.
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