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Review on anatomical medical images classification methods: Diagnostic value

Deep learning (DL) based convolutional neural network (CNN) has grown rapidly and become a selected choice for medical imaging fields. The paper reviews into three categories; 1) exploring the supervised machine learning methods, 2) reviews the limitations in deep learning, 3) and finally reviews th...

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Main Authors: Yousif, Ahmed Sabeeh, Sheikh, Usman Ullah, Omar, Zaid, Ahmed Mahmood, Omar
Format: Conference or Workshop Item
Published: 2021
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/94363/
http://dx.doi.org/10.1088/1742-6596/1804/1/012120
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id my.utm.94363
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spelling my.utm.943632022-03-31T15:14:53Z http://eprints.utm.my/id/eprint/94363/ Review on anatomical medical images classification methods: Diagnostic value Yousif, Ahmed Sabeeh Sheikh, Usman Ullah Omar, Zaid Ahmed Mahmood, Omar TK Electrical engineering. Electronics Nuclear engineering Deep learning (DL) based convolutional neural network (CNN) has grown rapidly and become a selected choice for medical imaging fields. The paper reviews into three categories; 1) exploring the supervised machine learning methods, 2) reviews the limitations in deep learning, 3) and finally reviews the majors deep learning techniques within a specific summarized on lesion classification-based DL in term of (application, method, type of lesion diseases classification, cons). 2021 Conference or Workshop Item PeerReviewed Yousif, Ahmed Sabeeh and Sheikh, Usman Ullah and Omar, Zaid and Ahmed Mahmood, Omar (2021) Review on anatomical medical images classification methods: Diagnostic value. In: 2nd International Conference of Modern Applications on Information and Communication Technology, ICMAICT 2020, 22 - 23 October 2020, Babylon-Hilla City. http://dx.doi.org/10.1088/1742-6596/1804/1/012120
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Yousif, Ahmed Sabeeh
Sheikh, Usman Ullah
Omar, Zaid
Ahmed Mahmood, Omar
Review on anatomical medical images classification methods: Diagnostic value
description Deep learning (DL) based convolutional neural network (CNN) has grown rapidly and become a selected choice for medical imaging fields. The paper reviews into three categories; 1) exploring the supervised machine learning methods, 2) reviews the limitations in deep learning, 3) and finally reviews the majors deep learning techniques within a specific summarized on lesion classification-based DL in term of (application, method, type of lesion diseases classification, cons).
format Conference or Workshop Item
author Yousif, Ahmed Sabeeh
Sheikh, Usman Ullah
Omar, Zaid
Ahmed Mahmood, Omar
author_facet Yousif, Ahmed Sabeeh
Sheikh, Usman Ullah
Omar, Zaid
Ahmed Mahmood, Omar
author_sort Yousif, Ahmed Sabeeh
title Review on anatomical medical images classification methods: Diagnostic value
title_short Review on anatomical medical images classification methods: Diagnostic value
title_full Review on anatomical medical images classification methods: Diagnostic value
title_fullStr Review on anatomical medical images classification methods: Diagnostic value
title_full_unstemmed Review on anatomical medical images classification methods: Diagnostic value
title_sort review on anatomical medical images classification methods: diagnostic value
publishDate 2021
url http://eprints.utm.my/id/eprint/94363/
http://dx.doi.org/10.1088/1742-6596/1804/1/012120
_version_ 1729703161619283968
score 13.211869

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