Convolutional Neural Networks in Medical Image Understanding

Megha Upreti; Chitra Pandey; Ankur Singh Bist; Buphest Rawat; Marviola Hardini

doi:10.34306/att.v3i2.188

Authors

Megha Upreti Graphic Era Hill University, Bhimtal Campus
Chitra Pandey Graphic Era Hill University, Bhimtal Campus
Ankur Singh Bist Graphic Era Hill University, Bhimtal Campus
Buphest Rawat Graphic Era Hill University, Bhimtal Campus
Marviola Hardini University of Raharja

DOI:

https://doi.org/10.34306/att.v3i2.188

Keywords:

Feature extraction, CNN, Muli-layer Neural Network, Medical data analysis

Abstract

In the era of social media images/pictures play a vital role. Facebook, whatsapp, instagram everywhere we see a lot of pictures nowadays. Along with social media, the pictures play a very important role in medical science. Medical Image can help in diagnosis, clinical treatment and teaching tasks. Traditional classification of images has reached an end because of its time taking nature and efforts made to extract, select and classify . This problem is solved with the help of CNN(Convolutional neural network).In medical science we have treatment for body anomalies that were not there before .Using the deep learning models of CNN we can detect the disease like Cancer ,Lung Infection and treat it. This article aims to provide a comprehensive survey of applications of CNNs in medical image understanding.

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