A novel framework for segmentation of stroke lesions in Diffusion Weighted MRI using multiple b-value data

Diffusion Weighted MR Imaging (DWI) is routinely used for early detection of cerebral ischemic stroke. DWI with higher b-values (b=2000) provide improved sensitivity, higher conspicuity and reduced artifacts and thus improve the detectability of smallest infarcts than conventional DWI (b=1000). We propose a novel framework for accurately detecting stroke regions by combining information from multiple sources:b2000, b1000 data and the apparent diffusion coefficient map. The detected lesions are finally segmented using an active contour approach. The proposed method was tested on 41 datasets acquired with different protocols. A comparison of our method with a leading method [3] validates the effectiveness of our approach. The median dice coefficient, sensitivity and specificity for stroke segmentation were 0.84, 87.07% and 99.90% respectively. The strength of the proposed method is its ability to capture (and accurately segment) the small (and large) lesions in the data which are often missed by segmentation methods operating on a single b-value data.