A stroke or “brain attack” occurs when the blood flow to an area of the brain is interrupted. In this article, ischemic stroke is detected and diagnosed using the following stages: noise reduction, enhancement, skull removal, feature extraction and k‐means clustering. The impulse noises in brain magnetic resonance imaging (MRI) image are reduced using directional filtering algorithm. The noise reduced brain image is further enhanced using oriented local histogram equalization technique. The skull is removed from the enhanced brain image. Features are extracted and stroke region is segmented using k‐means clustering and adaptive neuro fuzzy inference system (ANFIS) classifier. The main objective of this article is to develop a methodology for the detection of stroke using MRI brain images.

中文翻译：

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基于自适应神经模糊推理系统分类器的脑卒中计算机辅助检测与诊断方法

当流向大脑某个区域的血流中断时，就会发生中风或“脑部发作”。在本文中，使用以下阶段检测和诊断缺血性中风：降噪、增强、颅骨去除、特征提取和 k 均值聚类。使用定向滤波算法降低脑磁共振成像（MRI）图像中的脉冲噪声。使用定向局部直方图均衡技术进一步增强了降噪后的大脑图像。从增强的大脑图像中移除头骨。使用 k 均值聚类和自适应神经模糊推理系统 (ANFIS) 分类器提取特征并分割笔画区域。本文的主要目的是开发一种使用 MRI 脑图像检测中风的方法。