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Multichannel DenseNet Architecture for Classification of Mammographic Breast Density for Breast Cancer Detection.

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第一作者： Shivaji D,Pawar

第一单位： Department of Computer Science and Engineering, Lovely Professional University, Jalandhar, India.;SIES Graduate School of Technology, Navi Mumbai, India.

作者： Shivaji D,Pawar ^[1] ; Kamal K,Sharma ^[2] ; Suhas G,Sapate ^[3] ; Geetanjali Y,Yadav ^[4] ; Roobaea,Alroobaea ^[5] ; Sabah M,Alzahrani ^[5] ; Mustapha,Hedabou ^[6]

作者单位： Department of Computer Science and Engineering, Lovely Professional University, Jalandhar, India.;SIES Graduate School of Technology, Navi Mumbai, India. ^[1] School of Electronics and Electrical Engineering, Lovely Professional University, Jalandhar, India. ^[2] Department of Computer Science and Engineering, Annasaheb Dange College of Engineering and Technology, Sangli, India. ^[3] NMC Royal Medical Centre Karama, Abu Dhabi, United Arab Emirates. ^[4] Department Computer Science, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia. ^[5] School of Computer Science, Mohammed VI Polytechnic University, Ben Guerir, Morocco. ^[6]

关键词 BIRADS Density Classification DenseNet breast cancer deep learning mammographic breast density multichannel architecture

医学主题词人工智能(Artificial Intelligence);乳腺肿瘤(Breast Neoplasms);女(雌)性(Female);人类(Humans);乳房X线摄影术(Mammography)

DOI 10.3389/fpubh.2022.885212

PMID 35548086

发布时间 2022-08-07

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