Acute Stroke Brain Infarct Segmentation in DWI Images

Abstract

Acute ischemic infarct can be quickly identified with Diffusion Weighted Imaging (DWI) method. This research proposes to segment infarct areas in DWI dataset by applying Chan-Vese active contour and localized regionbased active contour algorithms. The knowledge about the infarct intensities of a particular problem dataset is gathered from the result in the first image slice and modified with some priori knowledge about the infarct in DWI images from an expert neurologist. The infarct segment areas from active contour algorithms in the consecutive slices that pass all three conditions: intensity, connectivity and size, are considered as infarct. Using an expert’s manual segment areas as our gold standard, the experiments reveal that our proposed approach should be able to assist human in infarct segmentation in DWI images. The proposed approach achieved good results with 0.8548 ± 0.0384 sensitivity, 0.8787 ± 0.0860 precision and 0.8511 ± 0.0475 DSC respectively. 