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Bioinformatics and Medical Applications
book

Bioinformatics and Medical Applications

by A. Suresh, S. Vimal, Y. Harold Robinson, Dhinesh Kumar Ramaswami, R. Udendhran
April 2022
Intermediate to advanced content levelIntermediate to advanced
352 pages
8h 39m
English
Wiley-Scrivener
Content preview from Bioinformatics and Medical Applications

9Brain Tumor Analysis Using Deep Learning: Sensor and IoT-Based Approach for Futuristic Healthcare

Rohit Rastogi1*, D.K. Chaturvedi2, Sheelu Sagar3, Neeti Tandon4 and Akshit Rajan Rastogi1

1Department of CSE, ABES Engineering College Ghaziabad, U.P., India

2Department of Electrical Engineering, Dayalbagh Educational Institute, Agra, India

3Amity International Business School, Amity University, Noida, U.P., India

4Vikram University, Ujjain, M.P, India

Abstract

One of the biggest problems in the quantitative evaluation of brain tumor treatment is finding the tumor type. The ambiguous magnetic resonance imaging (MRI) imaging strategy is currently the best classroom analysis tool for radiation-free brain tumors. Studies have shown that attractive imaging (MRI) features of different brain tumors can be used recently to make correction decisions. The manual part of a brain tumor to identify malignant growth is a tedious, tedious, and tedious task of teaching MRI clinical images. Recently, programming sections that use deep learning strategies are imaginative projects. These techniques yield the best results in the classroom and are easier to perform than other access methods. The ultimate goal of this investment is to use MRI images of the framed brain to create deep neural system models that can be isolated between different types of heart tumors. CNN is an iterative architecture that uses circular filters to perform complex operations in recent years. Precision is used as the basis ...

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Publisher Resources

ISBN: 9781119791836Purchase Link