Diagnosis of Brain Hemorrhage Using Artificial Neural Network

V. Davis¹ , S. Devane²

¹ Electronics and Telecommunication, Mumbai University, Mumbai, India.
² Electronics and Telecommunication, Mumbai University, Mumbai, India.

Correspondence should be addressed to: satish@dmce.ac.in.

Section:Research Paper, Product Type: Journal
Vol.5 , Issue.1 , pp.20-23, Apr-2017

Online published on Apr 30, 2017

Copyright © V. Davis, S. Devane . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Brain hemorrhage is a type of stroke which is caused due to bursting of artery in the brain and thus causing bleeding in the surrounding tissues. The major technique which is used for diagnosis of brain hemorrhage is through Computed Tomography (CT) scan. This dissertation investigates the possibility of diagnosing brain hemorrhage using an image segmentation of CT scan images using watershed algorithm and using the inputs extracted from the brain CT image to an artificial neural network for classification. The output generated as the type of brain hemorrhages, can be used to verify diagnosis also as a learning tool for trainee radiologists to minimize errors.

Key-Words / Index Term :
Brain hemorrhage, Intracerebral Hemorrhage, Subdural Hemorrhage, Extradural Hemorrhage, Subarachnoid Hemorrhage, Computed Tomography, X-rays

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