Paper Title
BRAIN TUMOUR IMAGE SEGMENTATION USING CONVOLUTIONAL NEURAL NETWORK
Article Identifiers
Authors
PAVITHRA S , Dr. T. Amalraj Victorie , M. Vasuki
Keywords
tumours, convolutional neural network, segmentation, images
Abstract
A tumor can manifest as a mass within the brain itself or in nearby structures such as nerves or the pituitary gland. These are typically the primary phases of brain tumors. However, tumors can also develop as a secondary phase when cancer from another part of the body metastasizes to the brain via the bloodstream. The secondary phases is known as metastatic brain tumors. CNNs (Convolutional Neural Network) plays a crucial role in analyzing medical images, including brain scans, to detect potential tumors. They excel at identifying pattern and features indicative of a tumor. Sometimes even surpassing the abilities of human radiologists. This is because CNNs are trained on vast datasets of brain scans, with or without tumor. Through this training, CNNs is learn to discern the subtle difference between healthy tissue and tumors formations. This capability aids in early and accurate diagnosis, improving patient outcomes.
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How To Cite (APA)
PAVITHRA S, Dr. T. Amalraj Victorie, & M. Vasuki (May-2024). BRAIN TUMOUR IMAGE SEGMENTATION USING CONVOLUTIONAL NEURAL NETWORK. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), e541-e544. https://ijnrd.org/papers/IJNRD2405457.pdf
Issue
Volume 9 Issue 5, May-2024
Pages : e541-e544
Other Publication Details
Paper Reg. ID: IJNRD_221620
Published Paper Id: IJNRD2405457
Downloads: 000121983
Research Area: Other
Country: puducherry, puducherry, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2405457.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405457
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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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