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Multiple Sclerosis Lesion Detection Using Constrained GMM and Curve Evolution
Joint Authors
Greenspan, Hayit
Goldberger, Jacob
Freifeld, Oren
Source
International Journal of Biomedical Imaging
Issue
Vol. 2009, Issue 2009 (31 Dec. 2009), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2009-09-10
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
This paper focuses on the detection and segmentation of Multiple Sclerosis (MS) lesions in magnetic resonance (MRI) brain images.
To capture the complex tissue spatial layout, a probabilistic model termed Constrained Gaussian Mixture Model (CGMM) is proposed based on a mixture of multiple spatially oriented Gaussians per tissue.
The intensity of a tissue is considered a global parameter and is constrained, by a parameter-tying scheme, to be the same value for the entire set of Gaussians that are related to the same tissue.
MS lesions are identified as outlier Gaussian components and are grouped to form a new class in addition to the healthy tissue classes.
A probability-based curve evolution technique is used to refine the delineation of lesion boundaries.
The proposed CGMM-CE algorithm is used to segment 3D MRI brain images with an arbitrary number of channels.
The CGMM-CE algorithm is automated and does not require an atlas for initialization or parameter learning.
Experimental results on both standard brain MRI simulation data and real data indicate that the proposed method outperforms previously suggested approaches, especially for highly noisy data.
American Psychological Association (APA)
Freifeld, Oren& Greenspan, Hayit& Goldberger, Jacob. 2009. Multiple Sclerosis Lesion Detection Using Constrained GMM and Curve Evolution. International Journal of Biomedical Imaging،Vol. 2009, no. 2009, pp.1-13.
https://search.emarefa.net/detail/BIM-492771
Modern Language Association (MLA)
Freifeld, Oren…[et al.]. Multiple Sclerosis Lesion Detection Using Constrained GMM and Curve Evolution. International Journal of Biomedical Imaging No. 2009 (2009), pp.1-13.
https://search.emarefa.net/detail/BIM-492771
American Medical Association (AMA)
Freifeld, Oren& Greenspan, Hayit& Goldberger, Jacob. Multiple Sclerosis Lesion Detection Using Constrained GMM and Curve Evolution. International Journal of Biomedical Imaging. 2009. Vol. 2009, no. 2009, pp.1-13.
https://search.emarefa.net/detail/BIM-492771
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-492771