Title: Automatic method recognition of ischemic stroke area on unenhanced CT brain images

Authors: Amina Fatima Zahra Yahiaoui; Abdelhafid Bessaid

Addresses: Department of Biomedical Engineering, Technology Faculty, University of Tlemcen, 13000, Algeria ' Department of Biomedical Engineering, Technology Faculty, University of Tlemcen, 13000, Algeria

Abstract: The purpose of this study is to develop an automatic method for detection of ischemic lesions on unenhanced CT images using bilateral comparison. Alberta stroke program early CT score (ASPECTS) has been proposed to help radiologists to make decisions regarding thrombolytic treatment. Only patients with favourable baseline benefited from endovascular therapy. The classification of the images into normal and abnormal depends on the features of left and right brain sides. The proposed method has five steps: preprocessing, segmentation of regions of interest, elimination of old infarcts and feature extraction. Features obtained from ten ROIs were then used to select the abnormal regions and to compute the corresponding ASPECTS score. The method was applied to 50 patients with infarctions of middle cerebral artery who presented to LA MEKERRA imaging centre. The performance of our method is quite satisfactory and has the potential to be used as second opinion in stroke diagnosis.

Keywords: CT scan; stroke detection; midline estimation; ASPECTS score; hemispheres comparison.

DOI: 10.1504/IJBET.2022.123148

International Journal of Biomedical Engineering and Technology, 2022 Vol.38 No.4, pp.319 - 333

Received: 24 Nov 2018
Accepted: 21 Feb 2019
Published online: 01 Jun 2022 *

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