Paper Title
Brain Stroke Detection Using Deep Learning
Article Identifiers
Authors
Pagala Parvez , Mr.V.Aravinda Rajan , Gonuguntla Chaitanya , Majjari Sai Siva , Kasarla Uday Kumar
Keywords
CT scans, Brain Structure, Deep learning Convolutional neural network, Image classification,Restnet-50
Abstract
Stroke is a serious medical disorder that needs to be diagnosed and treated quickly in order to reduce long- term effects and enhance patient outcomes. This study uses ResNet-50, a potent convolutional neural network architecture, to provide a unique method for the early diagnosis of brain strokes. By utilizing ResNet-50's deep learning capabilities, the suggested system is able to automatically evaluate medical imaging data, including CT and MRI scans, in order to spot possible stroke symptoms. The well- known ResNet-50 algorithm, which can handle complicated visual data, is customized to the unique properties of brain imaging in order to discriminate between areas of the brain that are healthy and those that have been harmed by a stroke. The medical photos are pre-processed as part of the protocol to improve pertinent characteristics, and finally using a carefully selected dataset of both healthy and stroke-affected brain pictures to train the ResNet- 50 model. The pre-trained ResNet-50 model is refined through the use of transfer learning approaches, improving its capacity to recognize and identify stroke patterns in a variety of patient data.
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How To Cite (APA)
Pagala Parvez, Mr.V.Aravinda Rajan, Gonuguntla Chaitanya, Majjari Sai Siva, & Kasarla Uday Kumar (April-2024). Brain Stroke Detection Using Deep Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), i513-i519. https://ijnrd.org/papers/IJNRD2404861.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : i513-i519
Other Publication Details
Paper Reg. ID: IJNRD_216428
Published Paper Id: IJNRD2404861
Downloads: 000121989
Research Area: Computer Science & TechnologyÂ
Country: Virudhunagar, Tamilnadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404861.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404861
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


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