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Cancer Management and Research Volume 13, 2021 - Issue
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Original Research

Deep Learning-Based Multi-Class Classification of Breast Digital Pathology Images

Weiming Mi1 Department of Automation, School of Information Science and Technology, Tsinghua University, Beijing, Peoples Republic of China;2 Beijing National Research Center for Information Science and Technology, Beijing, Peoples Republic of ChinaORCID Iconhttps://orcid.org/0000-0001-8655-1337
ORCID Icon,
Junjie Li3 Molecular Pathology Research Center, Department of Pathology, Peking Union Medical College Hospital (PUMCH), Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, Peoples Republic of China
,
Yucheng Guo4 Tsimage Medical Technology, Yantian Modern Industry Service Center, Shenzhen, Peoples Republic of China
,
Xinyu Ren3 Molecular Pathology Research Center, Department of Pathology, Peking Union Medical College Hospital (PUMCH), Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, Peoples Republic of China
,
Zhiyong Liang3 Molecular Pathology Research Center, Department of Pathology, Peking Union Medical College Hospital (PUMCH), Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, Peoples Republic of ChinaCorrespondence[email protected]
,
Tao Zhang1 Department of Automation, School of Information Science and Technology, Tsinghua University, Beijing, Peoples Republic of China;2 Beijing National Research Center for Information Science and Technology, Beijing, Peoples Republic of ChinaCorrespondence[email protected]
&
Hao Zou4 Tsimage Medical Technology, Yantian Modern Industry Service Center, Shenzhen, Peoples Republic of China;5 Center for Intelligent Medical Imaging & Health, Research Institute of Tsinghua University in Shenzhen, Shenzhen, Peoples Republic of China
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Pages 4605-4617 | Published online: 10 Jun 2021

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Mohaddeseh Chegini & Ali Mahlooji Far. (2023) Uncertainty-aware deep learning-based CAD system for breast cancer classification using ultrasound and mammography images. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 0:0, pages 1-17.
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Sheng-Kai Huang, Yu-Ting Yu, Chun-Rong Huang & Hsiu-Chi Cheng. (2024) Cross-Scale Fusion Transformer for Histopathological Image Classification. IEEE Journal of Biomedical and Health Informatics 28:1, pages 297-308.
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Mingshuai Li, Zhiqiu Hu, Song Qiu, Chenhao Zhou, Jialei Weng, Qiongzhu Dong, Xia Sheng, Ning Ren & Mei Zhou. (2023) Dual-branch hybrid encoding embedded network for histopathology image classification. Physics in Medicine & Biology 68:19, pages 195002.
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Cheng Wan, Rongrong Hua, Kunke Li, Xiangqian Hong, Dong Fang & Weihua Yang. (2023) Automatic Diagnosis of Different Types of Retinal Vein Occlusion Based on Fundus Images. International Journal of Intelligent Systems 2023, pages 1-13.
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Benjamin G. Gorman, Mark A. Lifson & Nahid Y. Vidal. (2023) Artificial intelligence and frozen section histopathology: A systematic review. Journal of Cutaneous Pathology 50:9, pages 852-859.
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Michael Co, Yik Ching Christy Lau, Yi Xuan Yvonne Qian, Man Chun Ryan Chan, Desiree Ka-ka Wong, Ka Ho Lui, Nicholas Yu Han So, Stephanie Wing Sum Tso, Yu Chee Lo, Woo Jung Lee & Elaine Wong. (2023) Artificial Intelligence in Histologic Diagnosis of Ductal Carcinoma In Situ. Mayo Clinic Proceedings: Digital Health 1:3, pages 267-275.
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Jakub R. Kaczmarzyk, Rajarsi Gupta, Tahsin M. Kurc, Shahira Abousamra, Joel H. Saltz & Peter K. Koo. (2023) ChampKit: A framework for rapid evaluation of deep neural networks for patch-based histopathology classification. Computer Methods and Programs in Biomedicine 239, pages 107631.
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Nehad M. Ibrahim, Batoola Ali, Fatimah Al Jawad, Majd Al Qanbar, Raghad I. Aleisa, Sukainah A. Alhmmad, Khadeejah R. Alhindi, Mona Altassan, Afnan F. Al-Muhanna, Hanoof M. Algofari & Farmanullah Jan. (2023) Breast Cancer Detection in the Equivocal Mammograms by AMAN Method. Applied Sciences 13:12, pages 7183.
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Dominika Petríková & Ivan Cimrák. (2023) Survey of Recent Deep Neural Networks with Strong Annotated Supervision in Histopathology. Computation 11:4, pages 81.
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Oleh Berezsky, Oleh Pitsun, Grygoriy Melnyk, Tamara Datsko, Ivan Izonin & Bohdan Derysh. (2023) An Approach toward Automatic Specifics Diagnosis of Breast Cancer Based on an Immunohistochemical Image. Journal of Imaging 9:1, pages 12.
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Haiyun Yu, Shaoze Luo, Junyu Ji, Zhiqiang Wang, Wenxue Zhi, Na Mo, Pingping Zhong, Chunyan He, Tao Wan & Yulan Jin. (2022) A Deep-Learning-Based Artificial Intelligence System for the Pathology Diagnosis of Uterine Smooth Muscle Tumor. Life 13:1, pages 3.
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Jie Liu, Hong Lai, Jinshu Ma & Shuchao Pang. (2022) ConTenNet: Quantum Tensor-augmented Convolutional Representations for Breast Cancer Histopathological Image Classification. ConTenNet: Quantum Tensor-augmented Convolutional Representations for Breast Cancer Histopathological Image Classification.
Inho Kim, Kyungmin Kang, Youngjae Song & Tae-Jung Kim. (2022) Application of Artificial Intelligence in Pathology: Trends and Challenges. Diagnostics 12:11, pages 2794.
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Mohamed Meselhy Eltoukhy, Khalid M. Hosny & Mohamed A. Kassem. (2022) Classification of Multiclass Histopathological Breast Images Using Residual Deep Learning. Computational Intelligence and Neuroscience 2022, pages 1-10.
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Kun Liu, Zhuolin Liu & Sidong Liu. (2022) Semi‐supervised breast histopathological image classification with self‐training based on non‐linear distance metric. IET Image Processing 16:12, pages 3164-3176.
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Yiheng Jiang, Shengbo Huang, Xinqing Zhu, Liang Cheng, Wenlong Liu, Qiwei Chen & Deyong Yang. (2022) Artificial Intelligence Meets Whole Slide Images: Deep Learning Model Shapes an Immune-Hot Tumor and Guides Precision Therapy in Bladder Cancer. Journal of Oncology 2022, pages 1-27.
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Ying Zou, Shannan Chen, Chao Che, Jianxin Zhang & Qiang Zhang. (2022) Breast cancer histopathology image classification based on dual-stream high-order network. Biomedical Signal Processing and Control 78, pages 104007.
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Yiqing Liu, Qiming He, Hufei Duan, Huijuan Shi, Anjia Han & Yonghong He. (2022) Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images. Sensors 22:16, pages 6053.
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Fahdi Kanavati, Shin Ichihara & Masayuki Tsuneki. (2022) A deep learning model for breast ductal carcinoma in situ classification in whole slide images. Virchows Archiv 480:5, pages 1009-1022.
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Muhammad Junaid Umer, Muhammad Sharif, Seifedine Kadry & Abdullah Alharbi. (2022) Multi-Class Classification of Breast Cancer Using 6B-Net with Deep Feature Fusion and Selection Method. Journal of Personalized Medicine 12:5, pages 683.
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Junjie Li, Weiming Mi, Yucheng Guo, Xinyu Ren, Hao Fu, Tao Zhang, Hao Zou & Zhiyong Liang. (2022) Artificial intelligence for histological subtype classification of breast cancer: combining multi‐scale feature maps and the recurrent attention model. Histopathology 80:5, pages 836-846.
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Alena Arlova, Chengcheng Jin, Abigail Wong-Rolle, Eric S. Chen, Curtis Lisle, G. Thomas Brown, Nathan Lay, Peter L. Choyke, Baris Turkbey, Stephanie Harmon & Chen Zhao. (2022) Artificial Intelligence-based Tumor Segmentation in Mouse Models of Lung Adenocarcinoma. Journal of Pathology Informatics 13, pages 100007.
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You Zhou, Yu-tong Ge, Xiao-lei Shi, Ke-yan Wu, Wei-wei Chen, Yan-bing Ding, Wei-ming Xiao, Dan Wang, Guo-tao Lu & Liang-hao Hu. (2022) Machine learning predictive models for acute pancreatitis: A systematic review. International Journal of Medical Informatics 157, pages 104641.
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Ying Zou, Shannan Chen, Qiule Sun, Bin Liu & Jianxin Zhang. (2021) DCET-Net: Dual-Stream Convolution Expanded Transformer for Breast Cancer Histopathological Image Classification. DCET-Net: Dual-Stream Convolution Expanded Transformer for Breast Cancer Histopathological Image Classification.
Fahdi Kanavati & Masayuki Tsuneki. (2021) Breast Invasive Ductal Carcinoma Classification on Whole Slide Images with Weakly-Supervised and Transfer Learning. Cancers 13:21, pages 5368.
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Weiming Mi, Tao Zhang & Jiaming Wang. (2021) TransRAM: A classification model of breast pathology images that imitates the diagnosis process of pathologists. TransRAM: A classification model of breast pathology images that imitates the diagnosis process of pathologists.

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