Detection of Tumors From MRI Brain Images Using CNN With Extensive Augmentation

Author:

Et.al Y Mohana Roopa

Abstract

Brain tumor is one of the most hazardous and lethal cancers which require effective detection of tumors for diagnosis, here medical image information is extremely essential. Mostly used images are Magnetic Resonance Image (MRI) images which provide a greater differentiation of assorted body soft tissues. In this paper we propose Deep learning architecture, specially the Convolutional Neural Network (CNN) along with augmentation techniques has been developed for Automatic classification of MRI images under study into tumor or no tumor with supervised learning. The proposed system has three stages at first, brain tumor images are re-sized(normalized) into equal size for effective training of model. Next, extensive data augmentation is employed, avoiding the lack of data problem when dealing with classification. Finally building CNN model for image classification.

Publisher

Auricle Technologies, Pvt., Ltd.

Subject

Computational Theory and Mathematics,Computational Mathematics,General Mathematics,Education

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Improved segmentation of brain tumors with data augmentation using MU-Net;Journal of Intelligent & Fuzzy Systems;2024-04-30

2. A Deep Learning and Powerful Computational Framework for Brain Cancer MRI Image Recognition;Journal of The Institution of Engineers (India): Series B;2023-12-05

3. A Comparative Analysis of PGGAN with Other Data Augmentation Technique for Brain Tumor Classification;2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC);2022-11-19

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3