Improving ductal carcinoma in situ classification by convolutional neural network with exponential linear unit and rank-
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ORIGINAL ARTICLE
Improving ductal carcinoma in situ classification by convolutional neural network with exponential linear unit and rank-based weighted pooling Yu-Dong Zhang1,2 Shui-Hua Wang2,7
· Suresh Chandra Satapathy3 · Di Wu5 · David S. Guttery4 · Juan Manuel Górriz6 ·
Received: 8 August 2020 / Accepted: 7 October 2020 © The Author(s) 2020
Abstract Ductal carcinoma in situ (DCIS) is a pre-cancerous lesion in the ducts of the breast, and early diagnosis is crucial for optimal therapeutic intervention. Thermography imaging is a non-invasive imaging tool that can be utilized for detection of DCIS and although it has high accuracy (~ 88%), it is sensitivity can still be improved. Hence, we aimed to develop an automated artificial intelligence-based system for improved detection of DCIS in thermographs. This study proposed a novel artificial intelligence based system based on convolutional neural network (CNN) termed CNN-BDER on a multisource dataset containing 240 DCIS images and 240 healthy breast images. Based on CNN, batch normalization, dropout, exponential linear unit and rank-based weighted pooling were integrated, along with L-way data augmentation. Ten runs of tenfold cross validation were chosen to report the unbiased performances. Our proposed method achieved a sensitivity of 94.08 ± 1.22%, a specificity of 93.58 ± 1.49 and an accuracy of 93.83 ± 0.96. The proposed method gives superior performance than eight state-of-theart approaches and manual diagnosis. The trained model could serve as a visual question answering system and improve diagnostic accuracy. Keywords Ductal carcinoma in situ · Thermal images · Deep learning · Convolutional neural network · Breast thermography · Exponential linear unit · Rank-based weighted pooling · Data augmentation · Color jittering · Visual question answering
Introduction Yu-Dong Zhang, Suresh Chandra Satapathy and Di Wu contributed equally to this paper. Yu-Dong Zhang, Suresh Chandra Satapathy and Di Wu are co-first authors.
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1
David S. Guttery [email protected] Juan Manuel Górriz [email protected]
Ductal carcinoma in situ (DCIS), also named intra-ductal carcinoma is a pre-cancerous lesion of cells that line the breast milk ducts, but have not spread into the surrounding breast tissue. DCIS is considered the earliest stage of breast cancer (Stage 0) [1], and although cure rates are 2
Shui-Hua Wang [email protected]
Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
3
Yu-Dong Zhang [email protected]
School of Computer Engg, KIIT Deemed to University, Bhubaneswar, India
4
Suresh Chandra Satapathy [email protected]
Leicester Cancer Research Center, University of Leicester, Leicester LE1 7RH, UK
5
University of Melbourne, Melbourne, VIC 3010, Australia
Di Wu [email protected]
6
Department of Signal Theory, Networking and Communications, University of Granada, Granada, Spain
School of Informatics, University of Leicester, Informatics Building, University R
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