Multiphase Region-based Active Contours for Semi-automatic Segmentation of Brain MRI Images (original) (raw)

2015, Proceedings of the 10th International Conference on Computer Vision Theory and Applications

Segmenting brain magnetic resonance (MRI) images of the brain into white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF) is an important problem in medical image analysis. The study of these regions can be useful for determining different brain disorders, assisting brain surgery, post-surgical analysis, saliency detection and for studying regions of interest. This paper presents a segmentation method that partitions a given brain MRI image into WM, GM and CSF regions through a multiphase region-based active contour method followed by a pixel correction thresholding stage. The proposed region-based active contour method is applied in order to partition the input image into four different regions. Three of those regions within the brain area are then chosen by intersecting a hand-drawn binary mask with the computed contours. Finally, an efficient thresholding-based pixel correction method is applied to the computed WM, GM and CSF regions to increase their accuracy. The segmentation results are compared with ground truths to show the performance of the proposed method.

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