Identification of Stroke Diagnostic Classification using Machine Learning


  • S. Sumathi, V. Agalya, K. Saranya


Cerebrum Hemorrhage is one among the stroke which happens by supported blasting of an itinerary within the mind, consequently inflicting oozing among the encircling tissues. CT (Computed Tomography) footage unit is performed to analyze the cracks in internal possessions of the body. It is always favored over imaging (Magnetic Resonance Imaging) footage because of result in extra accessibility to predict the early stroke. This footage unit is first preprocessed and performed for morphological tasks especially in watershed calculation. The developed image is counterfeit the neural system which is further used for characterization like discharge region and drain rate. In this paper, an extracted feature is classified by Artificial Neural Network and proposed methods with varying number of features are experimentally studied.