Automatic Shape Modelling with Applications in Medical Imaging
(2006) In Doctoral Theses in Mathematical Sciences 2006:6.- Abstract
- This thesis consists of two parts. The first part is devoted to automatic shape analysis and the second part is devoted to decision support systems in medical imaging. Shape models are widely used in segmentation and shape analysis. The thesis begins with a review of deformable models and the preliminaries of shape modelling. The criteria for Minimum Description Length (MDL) and a new optimization technique for MDL is presented. A new algorithm which uses affine shape to determine parameterisation for curves is also proposed. This part also includes a novel theory for prevention of clustering in correspondence optimization, based on shape variation invariant to curve parameterisation. The first part ends with a chapter on benchmarking... (More)
- This thesis consists of two parts. The first part is devoted to automatic shape analysis and the second part is devoted to decision support systems in medical imaging. Shape models are widely used in segmentation and shape analysis. The thesis begins with a review of deformable models and the preliminaries of shape modelling. The criteria for Minimum Description Length (MDL) and a new optimization technique for MDL is presented. A new algorithm which uses affine shape to determine parameterisation for curves is also proposed. This part also includes a novel theory for prevention of clustering in correspondence optimization, based on shape variation invariant to curve parameterisation. The first part ends with a chapter on benchmarking algorithms for automatic shape modelling. In the second part of the thesis three decision support systems are described. The first uses a 3D-shape model to segment out the heart in SPECT-images and can be used to diagnose heart infarction. The second system uses a static model for the diagnosis of Parkinson's disease from DatSCAN images. The third system handles the diagnosis of lung-embolie from lung-scint images. This part is concluded with a chapter on segmentation of medical images using 3D active shape models. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/25304
- author
- Ericsson, Anders LU
- supervisor
- opponent
-
- Professor Cootes, Tim, School of Medicine, University of Manchester
- organization
- publishing date
- 2006
- type
- Thesis
- publication status
- published
- subject
- keywords
- heart-infarction, lung-embolie, Parkinson, DaTSCAN, SPECT, SCINT, affine shape, MDL, automatic shape models, Deformable models, active shape, Mathematics, Matematik
- in
- Doctoral Theses in Mathematical Sciences
- volume
- 2006:6
- pages
- 191 pages
- publisher
- Centre for Mathematical Sciences, Lund University
- defense location
- Room MH:C, Centre for Mathematical Sciences, Sölvegatan 18, Lund Institute of Technology
- defense date
- 2006-09-22 13:15:00
- ISSN
- 1404-0034
- ISBN
- 91-628-6901-9
- language
- English
- LU publication?
- yes
- id
- 723df4c1-cc5b-4582-99fc-bc7834647213 (old id 25304)
- date added to LUP
- 2016-04-01 15:33:52
- date last changed
- 2019-05-21 13:33:45
@phdthesis{723df4c1-cc5b-4582-99fc-bc7834647213, abstract = {{This thesis consists of two parts. The first part is devoted to automatic shape analysis and the second part is devoted to decision support systems in medical imaging. Shape models are widely used in segmentation and shape analysis. The thesis begins with a review of deformable models and the preliminaries of shape modelling. The criteria for Minimum Description Length (MDL) and a new optimization technique for MDL is presented. A new algorithm which uses affine shape to determine parameterisation for curves is also proposed. This part also includes a novel theory for prevention of clustering in correspondence optimization, based on shape variation invariant to curve parameterisation. The first part ends with a chapter on benchmarking algorithms for automatic shape modelling. In the second part of the thesis three decision support systems are described. The first uses a 3D-shape model to segment out the heart in SPECT-images and can be used to diagnose heart infarction. The second system uses a static model for the diagnosis of Parkinson's disease from DatSCAN images. The third system handles the diagnosis of lung-embolie from lung-scint images. This part is concluded with a chapter on segmentation of medical images using 3D active shape models.}}, author = {{Ericsson, Anders}}, isbn = {{91-628-6901-9}}, issn = {{1404-0034}}, keywords = {{heart-infarction; lung-embolie; Parkinson; DaTSCAN; SPECT; SCINT; affine shape; MDL; automatic shape models; Deformable models; active shape; Mathematics; Matematik}}, language = {{eng}}, publisher = {{Centre for Mathematical Sciences, Lund University}}, school = {{Lund University}}, series = {{Doctoral Theses in Mathematical Sciences}}, title = {{Automatic Shape Modelling with Applications in Medical Imaging}}, volume = {{2006:6}}, year = {{2006}}, }