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Cancer Management and Research Volume 11, 2019 - Issue
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Original Research

Feasibility of computer-assisted diagnosis for breast ultrasound: the results of the diagnostic performance of S-detect from a single center in China

Chenyang Zhao1 Department of Ultrasound, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing 100730, China, [email protected]
,
Mengsu Xiao1 Department of Ultrasound, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing 100730, China, [email protected]
,
Yuxin Jiang1 Department of Ultrasound, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing 100730, China, [email protected]
,
He Liu1 Department of Ultrasound, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing 100730, China, [email protected]
,
Ming Wang1 Department of Ultrasound, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing 100730, China, [email protected]
,
Hongyan Wang1 Department of Ultrasound, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing 100730, China, [email protected]
,
Qiang Sun2 Department of Breast Surgery, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing 100730, China
&
Qingli Zhu1 Department of Ultrasound, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing 100730, China, [email protected]Correspondence[email protected]
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Pages 921-930 | Published online: 23 Jan 2019

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Ying Zhu, Weiwei Zhan, Xiaohong Jia, Juan Liu & Jianqiao Zhou. (2022) Clinical Application of Computer-Aided Diagnosis for Breast Ultrasonography: Factors That Lead to Discordant Results in Radial and Antiradial Planes. Cancer Management and Research 14, pages 751-760.
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Articles from other publishers (18)

Pengjie Song, Li Zhang, Longmei Bai, Qing Wang & Yanlei Wang. (2023) Diagnostic performance of ultrasound with computer-aided diagnostic system in detecting breast cancer. Heliyon 9:10, pages e20712.
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Y. Gu, W. Xu, Y. Liu, X. An, J. Li, L. Cong, L. Zhu, X. He, H. Wang & Y. Jiang. (2023) The feasibility of a novel computer-aided classification system for the characterisation and diagnosis of breast masses on ultrasound: a single-centre preliminary test study. Clinical Radiology 78:7, pages e516-e525.
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Mengwen Xia, Fulong Song, Yongfeng Zhao, Yongzhi Xie, Yafei Wen & Ping Zhou. (2023) Ultrasonography-based radiomics and computer-aided diagnosis in thyroid nodule management: performance comparison and clinical strategy optimization. Frontiers in Endocrinology 14.
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Yuqun Wang, Lei Tang, Pingping Chen & Man Chen. (2023) The Role of a Deep Learning-Based Computer-Aided Diagnosis System and Elastography in Reducing Unnecessary Breast Lesion Biopsies. Clinical Breast Cancer 23:3, pages e112-e121.
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Orlando Catalano, Roberta Fusco, Federica De Muzio, Igino Simonetti, Pierpaolo Palumbo, Federico Bruno, Alessandra Borgheresi, Andrea Agostini, Michela Gabelloni, Carlo Varelli, Antonio Barile, Andrea Giovagnoni, Nicoletta Gandolfo, Vittorio Miele & Vincenza Granata. (2023) Recent Advances in Ultrasound Breast Imaging: From Industry to Clinical Practice. Diagnostics 13:5, pages 980.
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Juan C Villa-Camacho, Masoud Baikpour & Shinn-Huey S Chou. (2023) Artificial Intelligence for Breast US. Journal of Breast Imaging 5:1, pages 11-20.
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Chunxiao Li, Yuanfan Guo, Liqiong Jia, Minghua Yao, Sihui Shao, Jing Chen, Yi Xu & Rong Wu. (2022) A Convolutional Neural Network Based on Ultrasound Images of Primary Breast Masses: Prediction of Lymph-Node Metastasis in Collaboration With Classification of Benign and Malignant Tumors. Frontiers in Physiology 13.
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Qi Wei, Yu-Jing Yan, Ge-Ge Wu, Xi-Rong Ye, Fan Jiang, Jie Liu, Gang Wang, Yi Wang, Juan Song, Zhi-Ping Pan, Jin-Hua Hu, Chao-Ying Jin, Xiang Wang, Christoph F. Dietrich & Xin-Wu Cui. (2022) The diagnostic performance of ultrasound computer-aided diagnosis system for distinguishing breast masses: a prospective multicenter study. European Radiology 32:6, pages 4046-4055.
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Qi Wei, Shu‐E Zeng, Li‐Ping Wang, Yu‐Jing Yan, Ting Wang, Jian‐Wei Xu, Meng‐Yi Zhang, Wen‐Zhi Lv, Christoph F. Dietrich & Xin‐Wu Cui. (2021) The Added Value of a Computer‐Aided Diagnosis System in Differential Diagnosis of Breast Lesions by Radiologists With Different Experience. Journal of Ultrasound in Medicine 41:6, pages 1355-1363.
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Kriti, Jitendra Virmani & Ravinder Agarwal. (2021) A Characterization Approach for the Review of CAD Systems Designed for Breast Tumor Classification Using B-Mode Ultrasound Images. Archives of Computational Methods in Engineering 29:3, pages 1485-1523.
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Chenyang Zhao, Mengsu Xiao, Li Ma, Xinhua Ye, Jing Deng, Ligang Cui, Fajin Guo, Min Wu, Baoming Luo, Qin Chen, Wu Chen, Jun Guo, Qian Li, Qing Zhang, Jianchu Li, Yuxin Jiang & Qingli Zhu. (2022) Enhancing Performance of Breast Ultrasound in Opportunistic Screening Women by a Deep Learning-Based System: A Multicenter Prospective Study. Frontiers in Oncology 12.
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Luca Nicosia, Francesca Addante, Anna Carla Bozzini, Antuono Latronico, Marta Montesano, Lorenza Meneghetti, Francesca Tettamanzi, Samuele Frassoni, Vincenzo Bagnardi, Rossella De Santis, Filippo Pesapane, Cristiana Iuliana Fodor, Mauro Giuseppe Mastropasqua & Enrico Cassano. (2022) Evaluation of computer-aided diagnosis in breast ultrasonography: Improvement in diagnostic performance of inexperienced radiologists. Clinical Imaging 82, pages 150-155.
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Zhu,MD Ying, Jia,MD Xiaohong, Dong,MD Yijie, Liu,MD Juan, Chen,MD Yilai, Yuan,MD Congcong, Zhan,MD Weiwei & Zhou,MD Jianqiao. (2022) Using S-Detect to Improve Breast Ultrasound: The Different Combined Strategies Based on Radiologist Experienc. ADVANCED ULTRASOUND IN DIAGNOSIS AND THERAPY 6:4, pages 180.
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Tommaso Vincenzo Bartolotta, Alessia Angela Maria Orlando, Maria Laura Di Vittorio, Francesco Amato, Mariangela Dimarco, Domenica Matranga & Raffaele Ienzi. (2020) S-Detect characterization of focal solid breast lesions: a prospective analysis of inter-reader agreement for US BI-RADS descriptors. Journal of Ultrasound 24:2, pages 143-150.
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Xin-Yi Wang, Li-Gang Cui, Jie Feng & Wen Chen. (2021) Artificial intelligence for breast ultrasound: An adjunct tool to reduce excessive lesion biopsy. European Journal of Radiology 138, pages 109624.
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Sihua Niu, Jianhua Huang, Jia Li, Xueling Liu, Dan Wang, Ruifang Zhang, Yingyan Wang, Huiming Shen, Min Qi, Yi Xiao, Mengyao Guan, Haiyan Liu, Diancheng Li, Feifei Liu, Xiuming Wang, Yu Xiong, Siqi Gao, Xue Wang & Jiaan Zhu. (2020) Application of ultrasound artificial intelligence in the differential diagnosis between benign and malignant breast lesions of BI-RADS 4A. BMC Cancer 20:1.
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Mengsu Xiao, Chenyang Zhao, Jianchu Li, Jing Zhang, He Liu, Ming Wang, Yunshu Ouyang, Yixiu Zhang, Yuxin Jiang & Qingli Zhu. (2020) Diagnostic Value of Breast Lesions Between Deep Learning-Based Computer-Aided Diagnosis System and Experienced Radiologists: Comparison the Performance Between Symptomatic and Asymptomatic Patients. Frontiers in Oncology 10.
Crossref
Liang Yongping, Zhang Juan, Ping Zhou, Zhao Yongfeng, Wengang Liu & Yifan Shi. (2020) Evaluation of the Quadri-Planes Method in Computer-Aided Diagnosis of Breast Lesions by Ultrasonography: Prospective Single-Center Study. JMIR Medical Informatics 8:5, pages e18251.
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