Diagnosis and precise localization of cardiomegaly disease using U-NET

This study examines an end-to-end technique which uses a Deep Convolutional Neural Network U-Net based architecture to detect Cardiomegaly disease. The learning phase is achieved by using Chest X-ray images extracted from the “ChestX-ray8” open source medical dataset. The Adaptive Histogram Equaliza...

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Main Authors:	Abdelilah Bouslama, Yassin Laaziz, Abdelhak Tali
Format:	Article
Language:	English
Published:	Elsevier 2020-01-01
Series:	Informatics in Medicine Unlocked
Subjects:	CXR Cardiomegaly CNN AHE U-Net
Online Access:	http://www.sciencedirect.com/science/article/pii/S2352914819304009

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record_format	Article
spelling	doaj-f5832eb4e1ad434ba78d86296dfb9eab2020-11-25T03:34:39ZengElsevierInformatics in Medicine Unlocked2352-91482020-01-0119100306Diagnosis and precise localization of cardiomegaly disease using U-NETAbdelilah Bouslama0Yassin Laaziz1Abdelhak Tali2Corresponding author.; Abdelmalek Essaadi University, LabTIC, ENSA, Tangier, MoroccoAbdelmalek Essaadi University, LabTIC, ENSA, Tangier, MoroccoAbdelmalek Essaadi University, LabTIC, ENSA, Tangier, MoroccoThis study examines an end-to-end technique which uses a Deep Convolutional Neural Network U-Net based architecture to detect Cardiomegaly disease. The learning phase is achieved by using Chest X-ray images extracted from the “ChestX-ray8” open source medical dataset. The Adaptive Histogram Equalization (AHE) method is deployed to enhance the contrast and brightness of the original images. These latter are compressed before undergoing a training stage to optimize computation time. By this method, we obtained a diagnostic accuracy greater than 93%, which outperforms published results for recognizing Cardiomegaly disease. In addition, with U-Net, precise localization of Cardiomegaly is possible, which is not the case in previous works.http://www.sciencedirect.com/science/article/pii/S2352914819304009CXRCardiomegalyCNNAHEU-Net
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Abdelilah Bouslama Yassin Laaziz Abdelhak Tali
spellingShingle	Abdelilah Bouslama Yassin Laaziz Abdelhak Tali Diagnosis and precise localization of cardiomegaly disease using U-NET Informatics in Medicine Unlocked CXR Cardiomegaly CNN AHE U-Net
author_facet	Abdelilah Bouslama Yassin Laaziz Abdelhak Tali
author_sort	Abdelilah Bouslama
title	Diagnosis and precise localization of cardiomegaly disease using U-NET
title_short	Diagnosis and precise localization of cardiomegaly disease using U-NET
title_full	Diagnosis and precise localization of cardiomegaly disease using U-NET
title_fullStr	Diagnosis and precise localization of cardiomegaly disease using U-NET
title_full_unstemmed	Diagnosis and precise localization of cardiomegaly disease using U-NET
title_sort	diagnosis and precise localization of cardiomegaly disease using u-net
publisher	Elsevier
series	Informatics in Medicine Unlocked
issn	2352-9148
publishDate	2020-01-01
description	This study examines an end-to-end technique which uses a Deep Convolutional Neural Network U-Net based architecture to detect Cardiomegaly disease. The learning phase is achieved by using Chest X-ray images extracted from the “ChestX-ray8” open source medical dataset. The Adaptive Histogram Equalization (AHE) method is deployed to enhance the contrast and brightness of the original images. These latter are compressed before undergoing a training stage to optimize computation time. By this method, we obtained a diagnostic accuracy greater than 93%, which outperforms published results for recognizing Cardiomegaly disease. In addition, with U-Net, precise localization of Cardiomegaly is possible, which is not the case in previous works.
topic	CXR Cardiomegaly CNN AHE U-Net
url	http://www.sciencedirect.com/science/article/pii/S2352914819304009
work_keys_str_mv	AT abdelilahbouslama diagnosisandpreciselocalizationofcardiomegalydiseaseusingunet AT yassinlaaziz diagnosisandpreciselocalizationofcardiomegalydiseaseusingunet AT abdelhaktali diagnosisandpreciselocalizationofcardiomegalydiseaseusingunet
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Diagnosis and precise localization of cardiomegaly disease using U-NET

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