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International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
ISSN Online 2393-8021ISSN Print 2394-1588Since 2014
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← Back to VOLUME 10, ISSUE 2, FEBRUARY 2023

MULTI-CLASSIFICATION OF BRAIN TUMOR IMAGES USING DEEP NEURAL NETWORK

Bhumika M, Anusha B, Raksha T M, Bharath R

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Abstract: One of the leading causes of cancer-related deaths globally is brain tumors. The categorization of brain tumors is a challenging scientific problem. Brain tumors come in a wide range of sizes, shapes, and intensities. It's possible for tumors from different pathological classifications to look similar. Brain tumors can be classified and diagnosed using a variety of imaging methods. Fortunately, due to its superior image quality and lack of ionizing radiation, Magnetic Resonance Imaging (MRI) is frequently used. Recent developments in deep learning have made it possible for radiologists to quickly analyse medical images using artificial intelligence (AI) techniques. In order to classify various types of brain tumors, CNN models can assist physicians and radiologists in validating their initial screening.

Keywords: Convolutional neural network , Deep learning ,Grid search, Hyper-parameter optimization, Tumor grading.

How to Cite:

[1] Bhumika M, Anusha B, Raksha T M, Bharath R, “MULTI-CLASSIFICATION OF BRAIN TUMOR IMAGES USING DEEP NEURAL NETWORK,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2023.10221

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