USG :: Ultrasonography

Combined diagnosis of multiparametric MRI-based deep learning models facilitates differentiating triple-negative breast cancer from fibroadenoma magnetic resonance BI-RADS 4 lesions

Hao-lin Yin, Yu Jiang, Zihan Xu, Hui-hui Jia, Guang-wu Lin

Journal of Cancer Research and Clinical Oncology.2023; 149(6): 2575. CrossRef

Comparison of S-Detect and thyroid imaging reporting and data system classifications in the diagnosis of cytologically indeterminate thyroid nodules

Ling Zhou, Lin-lin Zheng, Chuan-ju Zhang, Hong-fen Wei, Li-long Xu, Mu-rui Zhang, Qiang Li, Gao-fei He, Edem Prince Ghamor-Amegavi, Shi-yan Li

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

Y. Gu, W. Xu, Y. Liu, X. An, J. Li, L. Cong, L. Zhu, X. He, H. Wang, Y. Jiang

Toward AI-supported US Triage of Women with Palpable Breast Lumps in a Low-Resource Setting

Wendie A. Berg, Ana-Lilia López Aldrete, Ajit Jairaj, Juan Carlos Ledesma Parea, Claudia Yolanda García, R. Chad McClennan, Steven Yong Cen, Linda H. Larsen, M. Teresa Soler de Lara, Susan Love

Diagnostic Utility of Artificial Intelligence in Breast Ultrasound

Hyun Jo Youn, Hyeong Eun Jeong, Ha Rim Ahn, Sang Yull Kang, Sung Hoo Jung

Journal of Surgical Ultrasound.2023; 10(1): 8. CrossRef

Deep Learning–Based Computer-Aided Diagnosis for Breast Lesion Classification on Ultrasound: A Prospective Multicenter Study of Radiologists Without Breast Ultrasound Expertise

Ping He, Wen Chen, Ming-Yu Bai, Jun Li, Qing-Qing Wang, Li-Hong Fan, Jian Zheng, Chun-Tao Liu, Xiao-Rong Zhang, Xi-Rong Yuan, Peng-Jie Song, Li-Gang Cui

American Journal of Roentgenology.2023; 221(4): 450. CrossRef

Application of Artificial Intelligence in Breast Imaging: Current Landscape and Prospects

Korean Journal of Family Practice.2023; 13(4): 196. CrossRef

Diagnostic Performance of an Artificial Intelligence System in Breast Ultrasound

Avice M. O'Connell, Tommaso V. Bartolotta, Alessia Orlando, Sin‐Ho Jung, Jihye Baek, Kevin J. Parker

Journal of Ultrasound in Medicine.2022; 41(1): 97. CrossRef

The Added Value of a Computer‐Aided Diagnosis System in Differential Diagnosis of Breast Lesions by Radiologists With Different Experience

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

Journal of Ultrasound in Medicine.2022; 41(6): 1355. CrossRef

Evaluation of computer-aided diagnosis in breast ultrasonography: Improvement in diagnostic performance of inexperienced radiologists

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 Mastropas

The diagnostic performance of ultrasound computer-aided diagnosis system for distinguishing breast masses: a prospective multicenter study

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

Ultrasonographic morphological characteristics determined using a deep learning-based computer-aided diagnostic system of breast cancer

Young Seon Kim, Seung Eun Lee, Jung Min Chang, Soo-Yeon Kim, Young Kyung Bae

Diagnostic performance improvement with combined use of proteomics biomarker assay and breast ultrasound

Su Min Ha, Hong-Kyu Kim, Yumi Kim, Dong-Young Noh, Wonshik Han, Jung Min Chang

Breast Cancer Research and Treatment.2022; 192(3): 541. CrossRef

Clinical Application of Computer-Aided Diagnosis for Breast Ultrasonography: Factors That Lead to Discordant Results in Radial and Antiradial Planes

Ying Zhu, Weiwei Zhan, Xiaohong Jia, Juan Liu, Jianqiao Zhou

Cancer Management and Research.2022; Volume 14: 751. CrossRef

Predicting Breast Tumor Malignancy Using Deep ConvNeXt Radiomics and Quality-Based Score Pooling in Ultrasound Sequences

Mohamed A. Hassanien, Vivek Kumar Singh, Domenec Puig, Mohamed Abdel-Nasser

A Reproducible Deep-Learning-Based Computer-Aided Diagnosis Tool for Frontotemporal Dementia Using MONAI and Clinica Frameworks

Andrea Termine, Carlo Fabrizio, Carlo Caltagirone, Laura Petrosini

Diagnostic accuracy of S-Detect to breast cancer on ultrasonography: A meta-analysis (PRISMA)

An AI model of sonographer’s evaluation+ S-Detect + elastography + clinical information improves the preoperative identification of benign and malignant breast masses

Pengfei Sun, Ying Feng, Chen Chen, Andre Dekker, Linxue Qian, Zhixiang Wang, Jun Guo

Evolution of research trends in artificial intelligence for breast cancer diagnosis and prognosis over the past two decades: A bibliometric analysis

Differing benefits of artificial intelligence-based computer-aided diagnosis for breast US according to workflow and experience level

Si Eun Lee, Kyunghwa Han, Ji Hyun Youk, Jee Eun Lee, Ji-Young Hwang, Miribi Rho, Jiyoung Yoon, Eun-Kyung Kim, Jung Hyun Yoon

Using S-Detect to Improve Breast Ultrasound: The Different Combined Strategies Based on Radiologist Experienc

Zhu,MD Ying, Jia,MD Xiaohong, Dong,MD Yijie, Liu,MD Juan, Chen,MD Yilai, Yuan,MD Congcong, Zhan,MD Weiwei, Zhou,MD Jianqiao

ADVANCED ULTRASOUND IN DIAGNOSIS AND THERAPY.2022; 6(4): 180. CrossRef

Evaluating breast ultrasound S-detect image analysis for small focal breast lesions

Boyuan Xing, Xiangyi Chen, Yalin Wang, Shuang Li, Ying-Kui Liang, Dawei Wang

The Application of Computer Aided Optimization Design

Journal of Physics: Conference Series.2022; 2386(1): 012094. CrossRef

S-Detect characterization of focal solid breast lesions: a prospective analysis of inter-reader agreement for US BI-RADS descriptors

Tommaso Vincenzo Bartolotta, Alessia Angela Maria Orlando, Maria Laura Di Vittorio, Francesco Amato, Mariangela Dimarco, Domenica Matranga, Raffaele Ienzi

Deep learning-based computer-aided diagnosis in screening breast ultrasound to reduce false-positive diagnoses

Soo -Yeon Kim, Yunhee Choi, Eun -Kyung Kim, Boo-Kyung Han, Jung Hyun Yoon, Ji Soo Choi, Jung Min Chang

Artificial intelligence for breast ultrasound: An adjunct tool to reduce excessive lesion biopsy

European Journal of Radiology.2021; 138: 109624. CrossRef

3-D Res-CapsNet convolutional neural network on automated breast ultrasound tumor diagnosis

Huiling Xiang, Yao-Sian Huang, Chu-Hsuan Lee, Ting-Yin Chang Chien, Cheng-Kuang Lee, Lixian Liu, Anhua Li, Xi Lin, Ruey-Feng Chang

European Journal of Radiology.2021; 138: 109608. CrossRef

Association of Clinician Diagnostic Performance With Machine Learning–Based Decision Support Systems

Baptiste Vasey, Stephan Ursprung, Benjamin Beddoe, Elliott H. Taylor, Neale Marlow, Nicole Bilbro, Peter Watkinson, Peter McCulloch

U-Net and SegNet performances on lesion segmentation of breast ultrasonography images

Pedro Vianna, Ricardo Farias, Wagner Coelho de Albuquerque Pereira

Research on Biomedical Engineering.2021; 37(2): 171. CrossRef

Application of deep learning to establish a diagnostic model of breast lesions using two-dimensional grayscale ultrasound imaging

Nan Zhang, Xiao-Ting Li, Lu Ma, Zhao-Qing Fan, Ying-Shi Sun

Differential diagnosis of breast cancer assisted by S-Detect artificial intelligence system

Qun Xia, Yangmei Cheng, Jinhua Hu, Juxia Huang, Yi Yu, Hongjuan Xie, Jun Wang

Mathematical Biosciences and Engineering.2021; 18(4): 3680. CrossRef

Impact of Original and Artificially Improved Artificial Intelligence–based Computer-aided Diagnosis on Breast US Interpretation

Wendie A Berg, David Gur, Andriy I Bandos, Bronwyn Nair, Terri-Ann Gizienski, Cathy S Tyma, Gordon Abrams, Katie M Davis, Amar S Mehta, Grace Rathfon, Uzma X Waheed, Christiane M Hakim

Journal of Breast Imaging.2021; 3(3): 301. CrossRef

Künstliche Intelligenz in der Medizin und Gynäkologie – Holzweg oder Heilversprechen?

Artificial Intelligence in Medical Imaging of the Breast

Yu-Meng Lei, Miao Yin, Mei-Hui Yu, Jing Yu, Shu-E Zeng, Wen-Zhi Lv, Jun Li, Hua-Rong Ye, Xin-Wu Cui, Christoph F. Dietrich

Added value of deep learning-based computer-aided diagnosis and shear wave elastography to b-mode ultrasound for evaluation of breast masses detected by screening ultrasound

Min Young Kim, Soo-Yeon Kim, Yeon Soo Kim, Eun Sil Kim, Jung Min Chang

Evaluation of Different Breast Cancer Screening Strategies for High-Risk Women in Beijing, China: A Real-World Population-Based Study

Xi Zhang, Lei Yang, Shuo Liu, Huichao Li, Qingyu Li, Yangyang Cheng, Ning Wang, Jiafu Ji

Accuracy of ultrasonic artificial intelligence in diagnosing benign and malignant breast diseases

A combined ultrasonic B-mode and color Doppler system for the classification of breast masses using neural network

Xuejun Qian, Bo Zhang, Shaoqiang Liu, Yueai Wang, Xiaoqiong Chen, Jingyuan Liu, Yuzheng Yang, Xiang Chen, Yi Wei, Qisen Xiao, Jie Ma, K. Kirk Shung, Qifa Zhou, Lifang Liu, Zeyu Chen

Performance of Computer-Aided Diagnosis in Ultrasonography for Detection of Breast Lesions Less and More Than 2 cm: Prospective Comparative Study

Liang Yongping, Ping Zhou, Zhang Juan, Zhao Yongfeng, Wengang Liu, Yifan Shi

JMIR Medical Informatics.2020; 8(3): e16334. CrossRef

Evaluation of the Quadri-Planes Method in Computer-Aided Diagnosis of Breast Lesions by Ultrasonography: Prospective Single-Center Study

Liang Yongping, Zhang Juan, Ping Zhou, Zhao Yongfeng, Wengang Liu, Yifan Shi

JMIR Medical Informatics.2020; 8(5): e18251. CrossRef

Reducing the number of unnecessary biopsies of US-BI-RADS 4a lesions through a deep learning method for residents-in-training: a cross-sectional study

Chenyang Zhao, Mengsu Xiao, He Liu, Ming Wang, Hongyan Wang, Jing Zhang, Yuxin Jiang, Qingli Zhu

A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of breast masses on ultrasound

Hee Jeong Park, Sun Mi Kim, Bo La Yun, Mijung Jang, Bohyoung Kim, Ja Yoon Jang, Jong Yoon Lee, Soo Hyun Lee

Künstliche Intelligenz in der Medizin – Holzweg oder Heilversprechen?

Computer‐Aided Diagnosis of Solid Breast Lesions With Ultrasound: Factors Associated With False‐negative and False‐positive Results

Jia‐yi Wu, Zi‐zhuo Zhao, Wen‐yue Zhang, Ming Liang, Bing Ou, Hai‐yun Yang, Bao‐ming Luo

Journal of Ultrasound in Medicine.2019; 38(12): 3193. CrossRef

Performance and Reading Time of Automated Breast US with or without Computer-aided Detection

Shanling Yang, Xican Gao, Liwen Liu, Rui Shu, Jingru Yan, Ge Zhang, Yao Xiao, Yan Ju, Ni Zhao, Hongping Song

Novel insights into breast cancer progression and metastasis: A multidisciplinary opportunity to transition from biology to clinical oncology

Manuel Scimeca, Nicoletta Urbano, Rita Bonfiglio, Andrea Duggento, Nicola Toschi, Orazio Schillaci, Elena Bonanno

Biochimica et Biophysica Acta (BBA) - Reviews on Cancer.2019; 1872(1): 138. CrossRef

Reliability Studies of Different Readers Using Computer Aided Diagnosis System in Ultrasound for Determining Identical Lesions in a Breast Phantom

Nari Choi, Bong Joo Kang, Na Young Jung, Sung Hun Kim, Jung Min Lee, Ga Eun Park

Iranian Journal of Radiology.2019;[Epub] CrossRef

Screening Breast Ultrasound Using Handheld or Automated Technique in Women with Dense Breasts

Journal of Breast Imaging.2019; 1(4): 283. CrossRef

A Comparative Study of the Diagnostic Performance of Evaluating Breast Masses for Breast Surgeons versus S-DetectTM(Samsung Medison Co., Ltd, Seoul, Korea)

Haram Kim, Eiyoung Kwon, Youngsam Park, Eunhye Choi, Mijin Kim, Cheolseung Kim

Journal of Surgical Ultrasound.2019; 6(2): 58. CrossRef

Breast Ultrasound Computer-Aided Diagnosis: Analysis of Types of Errors

Min Kyung Jeong, Bong Joo Kang, Eunjeong Kim, Sung Hun Kim

Journal of the Korean Society of Radiology.2018; 79(3): 114. CrossRef