Brain Stroke Detection Using CNN Algorithm

Strokes damage the central nervous system and are one of the leading causes of death today. Compared with several kinds of stroke, hemorrhagic and ischemic causes have a negative impact on the human central nervous system. One of the cerebrovascular health conditions, stroke has a significant impact on a person’s life and health. In order to diagnose and treat stroke, brain CT scan images must undergo electronic quantitative analysis. An essential tool for damage revelation is provided by deep neural networks, which have a tremendous capacity for data learning. In this paper, we aim to detect brain strokes with the help of CT-Scan images by using a convolutional neural network. After training and testing the model on a CT-scan dataset comprising 2551 images, we obtained the best accuracy of 90%.