Suresh Chandra Satapathy*, Steven Lawrence Fernandes and Hong Lin
Stroke is one of the major causes for the momentary/permanent disability in the human community. Usually, stroke will originate in the brain section because of the neurological deficit and this kind of brain abnormality can be predicted by scrutinizing the periphery of brain region. Magnetic Resonance Image (MRI) is the extensively considered imaging procedure to record the interior sections of the brain to support visual inspection process. In the proposed work, a semi-automated examination procedure is proposed to inspect the province and the severity of the stroke lesion using the MRI. Recently discovered heuristic approach called the Social Group Optimization (SGO) algorithm is considered to pre-process the test image based on a chosen image multi-thresholding procedure. Later, a chosen segmentation procedure is considered in the post-processing section to mine the stroke lesion from the pre-processed image. In this paper, the pre-processing work is executed with the well known thresholding approaches, such as Shannonâ€™s entropy, Kapurâ€™s entropy and Otsuâ€™s function. Similarly, the post-processing task is executed using most successful procedures, such as level set, active contour and watershed algorithm. The proposed procedure is experimentally inspected using the benchmark brain stroke database known as Ischemic Stroke Lesion Segmentation (ISLES 2015) challenge database. The results of this experimental work authenticates that, Shannonâ€™s approach along with the LS segmentation offers superior average values compared with the other approaches considered in this research work.
Brain stroke; Social group optimization Pre-processing; Post-processing; Performance assessment
P.V.P. Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, Sahyadri College of Engineering and Management - Department of Electronics and Communication Engineering Mangalore, Karnataka, University of Houston-Downtown - Department of Computer and Mathematical Sciences Houston, Texas