A two layer case-based reasoning architecture for medical image understanding

Author(s):  
Morten Grimnes ◽  
Agnar Aamodt
1996 ◽  
Vol 29 (7) ◽  
pp. 179-184
Author(s):  
Tatjana Zrimec ◽  
Claude Sammut

2021 ◽  
Vol 3 (2) ◽  
pp. 6-12
Author(s):  
Megha Upreti ◽  
Chitra Pandey ◽  
Ankur Singh Bist ◽  
Buphest Rawat ◽  
Marviola Hardini

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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