Model-based segmentation methods for analysis of 2d and 3d ultrasound images and sequences
<p>This thesis describes extensions to 2D and 3D model-based segmentation algorithms for the analysis of ultrasound images and sequences.</p> <p>Starting from a common 2D&plus;t "track-to-last" algorithm, it is shown that the typical method of searching for bounda...
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
2014
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| الموضوعات: |
| _version_ | 1826304278185115648 |
|---|---|
| author | Stebbing, R |
| author2 | Noble, J |
| author_facet | Noble, J Stebbing, R |
| author_sort | Stebbing, R |
| collection | OXFORD |
| description | <p>This thesis describes extensions to 2D and 3D model-based segmentation algorithms for the analysis of ultrasound images and sequences.</p> <p>Starting from a common 2D&plus;t "track-to-last" algorithm, it is shown that the typical method of searching for boundary candidates perpendicular to the model contour is unnecessary if, for each boundary candidate, its corresponding position on the model contour is optimised jointly with the model contour geometry. With this observation, two 2D&plus;t segmentation algorithms, which accurately recover boundary displacements and are capable of segmenting arbitrarily long sequences, are formulated and validated.</p> <p>Generalising to 3D, subdivision surfaces are shown to be natural choices for continuous model surfaces, and the algorithms necessary for joint optimisation of the correspondences and model surface geometry are described. Three applications of 3D model-based segmentation for ultrasound image analysis are subsequently presented and assessed: skull segmentation for fetal brain image analysis; face segmentation for shape analysis, and single-frame left ventricle (LV) segmentation from echocardiography images for volume measurement. A framework to perform model-based segmentation of <em>multiple</em> 3D sequences - while jointly optimising an underlying linear basis shape model - is subsequently presented for the challenging application of right ventricle (RV) segmentation from 3D&plus;t echocardiography sequences. Finally, an algorithm to automatically select boundary candidates <em>independent</em> of a model surface estimate is described and presented for the task of LV segmentation.</p> <p>Although motivated by challenges in ultrasound image analysis, the conceptual contributions of this thesis are general and applicable to model-based segmentation problems in many domains. Moreover, the components are modular, enabling straightforward construction of application-specific formulations for new clinical problems as they arise in the future.</p> |
| first_indexed | 2024-03-07T06:15:22Z |
| format | Thesis |
| id | oxford-uuid:f0e855ca-5ed9-4e40-994c-9b470d5594bf |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T06:15:22Z |
| publishDate | 2014 |
| record_format | dspace |
| spelling | oxford-uuid:f0e855ca-5ed9-4e40-994c-9b470d5594bf2022-03-27T11:51:45ZModel-based segmentation methods for analysis of 2d and 3d ultrasound images and sequencesThesishttp://purl.org/coar/resource_type/c_db06uuid:f0e855ca-5ed9-4e40-994c-9b470d5594bfMathematical modeling (engineering)Image understandingInformation engineeringEnglishOxford University Research Archive - Valet2014Stebbing, RNoble, J<p>This thesis describes extensions to 2D and 3D model-based segmentation algorithms for the analysis of ultrasound images and sequences.</p> <p>Starting from a common 2D&plus;t "track-to-last" algorithm, it is shown that the typical method of searching for boundary candidates perpendicular to the model contour is unnecessary if, for each boundary candidate, its corresponding position on the model contour is optimised jointly with the model contour geometry. With this observation, two 2D&plus;t segmentation algorithms, which accurately recover boundary displacements and are capable of segmenting arbitrarily long sequences, are formulated and validated.</p> <p>Generalising to 3D, subdivision surfaces are shown to be natural choices for continuous model surfaces, and the algorithms necessary for joint optimisation of the correspondences and model surface geometry are described. Three applications of 3D model-based segmentation for ultrasound image analysis are subsequently presented and assessed: skull segmentation for fetal brain image analysis; face segmentation for shape analysis, and single-frame left ventricle (LV) segmentation from echocardiography images for volume measurement. A framework to perform model-based segmentation of <em>multiple</em> 3D sequences - while jointly optimising an underlying linear basis shape model - is subsequently presented for the challenging application of right ventricle (RV) segmentation from 3D&plus;t echocardiography sequences. Finally, an algorithm to automatically select boundary candidates <em>independent</em> of a model surface estimate is described and presented for the task of LV segmentation.</p> <p>Although motivated by challenges in ultrasound image analysis, the conceptual contributions of this thesis are general and applicable to model-based segmentation problems in many domains. Moreover, the components are modular, enabling straightforward construction of application-specific formulations for new clinical problems as they arise in the future.</p> |
| spellingShingle | Mathematical modeling (engineering) Image understanding Information engineering Stebbing, R Model-based segmentation methods for analysis of 2d and 3d ultrasound images and sequences |
| title | Model-based segmentation methods for analysis of 2d and 3d ultrasound images and sequences |
| title_full | Model-based segmentation methods for analysis of 2d and 3d ultrasound images and sequences |
| title_fullStr | Model-based segmentation methods for analysis of 2d and 3d ultrasound images and sequences |
| title_full_unstemmed | Model-based segmentation methods for analysis of 2d and 3d ultrasound images and sequences |
| title_short | Model-based segmentation methods for analysis of 2d and 3d ultrasound images and sequences |
| title_sort | model based segmentation methods for analysis of 2d and 3d ultrasound images and sequences |
| topic | Mathematical modeling (engineering) Image understanding Information engineering |
| work_keys_str_mv | AT stebbingr modelbasedsegmentationmethodsforanalysisof2dand3dultrasoundimagesandsequences |