Publiora

Menghubungkan ke Publiora...

Publiora

Convolutional Neural Networks in Medical Image Understanding

Upreti, MeghaPandey, ChitraBist, Ankur SinghRawat, BuphestHardini, MarviolaHardini, Marviola
Aptisi Transactions on Technopreneurship (ATT) (Sinta 1)Vol. 0 No. 01 September 2021
DOI10.34306/att.v3i2.188

Abstrak

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.

Kata Kunci

Feature extractionCNNMuli-layer Neural NetworkMedical data analysis

Cari jurnal yang tepat untuk naskah Anda

MatchMind AI mencocokkan abstrak naskah Anda dengan ribuan jurnal terakreditasi dan menampilkan rekomendasi terbaik beserta alasannya.

Coba MatchMind

Lihat profil lengkap jurnal ini

Waktu review, biaya APC, statistik sitasi, indeksasi Scopus, dan banyak lagi.

Buka Aptisi Transactions on Technopreneurship (ATT)

Artikel ini juga tersedia di situs resmi jurnal.

Convolutional Neural Networks in Medical Image Understanding | Aptisi Transactions on Technopreneurship (ATT) | Publiora