NDLI: Statistical Shape Model-based Segmentation of brain MRI Images

Content Provider	IEEE Xplore Digital Library
Author	Bailleul, J. Su Ruan Constans, J.-M.
Copyright Year	2007
Description	Author affiliation: GREYC CNRS UMR 6072, Caen (Bailleul, J.)
Abstract	We propose a segmentation method that automatically delineates structures contours from 3D brain MRI images using a statistical shape model. We automatically build this 3D point distribution model (PDM) in applying a minimum description length (MDL) annotation to a training set of shapes, obtained by registration of a 3D anatomical atlas over a set of patients brain MRIs. Delineation of any structure from a new MRI image is first initialized by such registration. Then, delineation is achieved in iterating two consecutive steps until the 3D contour reaches idempotence. The first step consists in applying an intensity model to the latest shape position so as to formulate a closer guess: our model requires far less priors than standard model in aiming at direct interpretation rather than compliance to learned contexts. The second step consists in enforcing shape constraints onto previous guess so as to remove all bias induced by artifacts or low contrast on current MRI. For this, we infer the closest shape instance from the PDM shape space using a new estimation method which accuracy is significantly improved by a huge increase in the model resolution and by a depth-search in the parameter space. The delineation results we obtained are very encouraging and show the interest of the proposed framework.
Starting Page	5255
Ending Page	5258
File Size	1214526
Page Count	4
File Format	PDF
ISBN	9781424407873
ISSN	1557170X
DOI	10.1109/IEMBS.2007.4353527
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-22
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brain modeling Image segmentation Magnetic resonance imaging Deformable models Context modeling Active shape model Uncertainty Prototypes Biomedical imaging Robustness
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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