Segmentation of medical images using three-dimensional active shape models
(2005) 14th Scandinavian Conference on Image Analysis 3540. p.719-728- Abstract
- In this paper a fully automated segmentation system for the femur in the knee in Magnetic Resonance Images and the brain in Single Photon Emission Computed Tomography images is presented. To do this several data sets were first segmented manually. The resulting structures were represented by unorganised point clouds. With level set methods surfaces were fitted to these point clouds. The iterated closest point algorithm was then applied to establish correspondences between the different surfaces. Both surfaces and correspondences were used to build a three dimensional statistical shape model. The resulting model is then used to automatically segment structures in subsequent data sets through three dimensional Active Shape Models. The result... (More)
- In this paper a fully automated segmentation system for the femur in the knee in Magnetic Resonance Images and the brain in Single Photon Emission Computed Tomography images is presented. To do this several data sets were first segmented manually. The resulting structures were represented by unorganised point clouds. With level set methods surfaces were fitted to these point clouds. The iterated closest point algorithm was then applied to establish correspondences between the different surfaces. Both surfaces and correspondences were used to build a three dimensional statistical shape model. The resulting model is then used to automatically segment structures in subsequent data sets through three dimensional Active Shape Models. The result of the segmentation is promising, but the quality of the segmentation is dependent on the initial guess. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/231566
- author
- Josephson, Klas LU ; Ericsson, Anders LU and Karlsson, Johan LU
- organization
- publishing date
- 2005
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Image Analysis (Lecture Notes in Computer Science)
- editor
- Kalviainen, Heikki ; Parkkinen, Jussi and Kaarna, Arto
- volume
- 3540
- pages
- 719 - 728
- publisher
- Springer
- conference name
- 14th Scandinavian Conference on Image Analysis
- conference location
- Joensuu, Finland
- conference dates
- 2005-06-19 - 2005-06-22
- external identifiers
-
- wos:000230372500073
- scopus:26444495560
- ISSN
- 1611-3349
- 0302-9743
- ISBN
- 978-3-540-26320-3
- DOI
- 10.1007/11499145_73
- language
- English
- LU publication?
- yes
- id
- c97fa77a-6789-48d2-9833-71e2b93bb953 (old id 231566)
- date added to LUP
- 2016-04-01 11:49:49
- date last changed
- 2024-03-25 15:21:40
@inproceedings{c97fa77a-6789-48d2-9833-71e2b93bb953,
abstract = {{In this paper a fully automated segmentation system for the femur in the knee in Magnetic Resonance Images and the brain in Single Photon Emission Computed Tomography images is presented. To do this several data sets were first segmented manually. The resulting structures were represented by unorganised point clouds. With level set methods surfaces were fitted to these point clouds. The iterated closest point algorithm was then applied to establish correspondences between the different surfaces. Both surfaces and correspondences were used to build a three dimensional statistical shape model. The resulting model is then used to automatically segment structures in subsequent data sets through three dimensional Active Shape Models. The result of the segmentation is promising, but the quality of the segmentation is dependent on the initial guess.}},
author = {{Josephson, Klas and Ericsson, Anders and Karlsson, Johan}},
booktitle = {{Image Analysis (Lecture Notes in Computer Science)}},
editor = {{Kalviainen, Heikki and Parkkinen, Jussi and Kaarna, Arto}},
isbn = {{978-3-540-26320-3}},
issn = {{1611-3349}},
language = {{eng}},
pages = {{719--728}},
publisher = {{Springer}},
title = {{Segmentation of medical images using three-dimensional active shape models}},
url = {{https://lup.lub.lu.se/search/files/2660779/1245446.pdf}},
doi = {{10.1007/11499145_73}},
volume = {{3540}},
year = {{2005}},
}