Sciweavers

Share
ISBI
2004
IEEE

A Probabilistic Framework for the Detection and Tracking in Time of Multiple Sclerosis Lesions

11 years 11 months ago
A Probabilistic Framework for the Detection and Tracking in Time of Multiple Sclerosis Lesions
A novel statistical scheme for the automatic detection and tracking in time of relapsing-remitting multiple sclerosis (MS) lesions in image sequences is described. Coherent space-time regions in a four-dimensional feature space (intensity, position (x,y), and time) are extracted by unsupervised clustering using Gaussian mixture modeling. The segments in the sequence pertaining to lesions are automatically detected by context-based classification mechanisms. Lesion segmentation and tracking are performed in a unified manner and not separately, as in other works. A model adaptation stage, in which spacetime regions are merged, is introduced for the improvement of lesions' delineation. Qualitative and quantitative results for a sequence of 24 images are shown. The framework's results were validated by comparison to an expert's manual delineation.
Allon Shahar, Hayit Greenspan
Added 20 Nov 2009
Updated 20 Nov 2009
Type Conference
Year 2004
Where ISBI
Authors Allon Shahar, Hayit Greenspan
Comments (0)
books