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2007
IEEE

Lesion Detection in Noisy Mr Brain Images Using Constrained Gmm and Active Contours

9 years 3 months ago
Lesion Detection in Noisy Mr Brain Images Using Constrained Gmm and Active Contours
This paper focuses on the detection and segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. The proposed method performs healthy tissue segmentation using a probabilistic model for normal brain images. MS lesions are simultaneously identified as outlier Gaussian components. The probablistic model, termed constrained-GMM, is based on a mixture of many spatially-oriented Gaussians per tissue. The intensity of a tissue is considered a global parameter and is constrained to be the same value for a set of related Gaussians per tissue. An active contour algorithm is used to delineate lesion boundaries. Experimental results on both standard brain MR simulation data and real data, indicate that our method outperforms previously suggested approaches especially for highly noisy data.
Oren Freifeld, Hayit Greenspan, Jacob Goldberger
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where ISBI
Authors Oren Freifeld, Hayit Greenspan, Jacob Goldberger
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