Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network

The rapid advancement in pattern recognition via the deep learning method has made it possible to develop an autonomous medical image classification system. This system has proven robust and accurate in classifying most pathological features found in a medical image, such as airspace opacity, mass,...

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Bibliographic Details
Main Authors: Md. Ali, Mohd. Adli, Abidin, Mohd Radhwan, Nik Muhamad Affendi, Nik Arsyad, Abdullah, Hafidzul, Rosman, Daaniyal Reesha, Badrud'din, Nu'man, Kemi, Faiz, Hayati, Farid
Format: Article
Language:en
en
Published: Faculty of Engineering, IIUM 2021
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Online Access:http://irep.iium.edu.my/90919/7/90919_Classification%20of%20chest%20radiographs%20using%20novel%20anomalous%20saliency%20map.pdf
http://irep.iium.edu.my/90919/13/90919_Classification%20of%20chest%20radiographs%20using%20novel%20anomalous%20saliency%20map_Scopus.pdf
http://irep.iium.edu.my/90919/
https://journals.iium.edu.my/ejournal/index.php/iiumej/article/view/1752
https://doi.org/10.31436/iiumej.v22i2.1752
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