Automatic nodule identification and differentiation in ultrasound videos to facilitate per-nodule examination
Siyuan Jiang, Yan Ding, Yuling Wang, Lei Xu, Wenli Dai, Wanru Chang, Jianfeng Zhang, Jie Yu, Jianqiao Zhou, Chunquan Zhang, Ping Liang, Dexing Kong
备注：
The authors wish to withdraw this manuscript as it requires major revisions that substantially change the methodology and conclusions. A significantly updated version of this work may be submitted elsewhere at a later date. Thank you for your understanding
Ultrasound is a vital diagnostic technique in health screening, with the advantages of non-invasive, cost-effective, and radiation free, and therefore is widely applied in the diagnosis of nodules. However, it relies heavily on the expertise and clinical experience of the sonographer. In ultrasound images, a single nodule might present heterogeneous appearances in different cross-sectional views which makes it hard to perform per-nodule examination. Sonographers usually discriminate different nodules by examining the nodule features and the surrounding structures like gland and duct, which is cumbersome and time-consuming. To address this problem, we collected hundreds of breast ultrasound videos and built a nodule reidentification system that consists of two parts: an extractor based on the deep learning model that can extract feature vectors from the input video clips and a real-time clustering algorithm that automatically groups feature vectors by nodules. The system obtains satisfactory results and exhibits the capability to differentiate ultrasound videos. As far as we know, it's the first attempt to apply re-identification technique in the ultrasonic field.
A Deep Learning Framework for Thyroid Nodule Segmentation and Malignancy Classification from Ultrasound Images
Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, UK（沃里克大学计算机科学系组织图像分析中心，英国）；Royal Stoke University Hospital, University Hospitals of North Midlands, UK（北中部大学医院皇家斯托医院，英国）
Multistep Automated Data Labelling Procedure (MADLaP) for Thyroid Nodules on Ultrasound: An Artificial Intelligence Approach for Automating Image Annotation
Duke University（杜克大学）；Duke University Medical Center（杜克大学医学中心）
Beyond Point Annotation: A Weakly Supervised Network Guided by Multi-Level Labels Generated from Four-Point Annotation for Thyroid Nodule Segmentation in Ultrasound Image
Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China（机器人科学与工程学院，东北大学，沈阳，中国）；Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, Canada（生物医学工程系，萨斯喀彻温大学，萨斯喀彻温，加拿大）；Department of Ultrasound, Shengjing Hospital of China Medical University, Shenyang, China（超声科，中国医科大学附属盛京医院，沈阳，中国）
Calibrated Selective Prediction Using Deep Ensembles for ROI-Based Thyroid Nodule Ultrasound Classification Under Dataset Shift: A Retrospective Evaluation
Daffodil International University（达福德国际大学）；Birmingham City University（伯明翰城市大学）
STACT-Time: Spatio-Temporal Cross Attention for Cine Thyroid Ultrasound Time Series Classification
Medical \& Imaging Informatics, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles (UCLA), CA, USA Department of Bioengineering, UCLA, Los Angeles, CA, USA Department of Electrical；Computer Engineering, UCLA, Los Angeles, CA, USA Department of Radiological Sciences, UCLA, Los Angeles, CA, USA
FetalNet: Multi-task Deep Learning Framework for Fetal Ultrasound Biometric Measurements
Sano Centre for Computational Medicine（萨诺计算医学中心）；Warsaw University of Technology（华沙理工大学）；Fetai Health Ltd.（Fetai健康有限公司）；Medical University of Warsaw（华沙医科大学）；Tooploox（Tooploox公司）
Multi-Center Study on Deep Learning-Assisted Detection and Classification of Fetal Central Nervous System Anomalies Using Ultrasound Imaging
School of Mathematics and Statistics, Xiamen University of Technology（厦门理工学院数学与统计学院）；Department of Obstetrics, Xiamen University Affiliated First Hospital（厦门大学附属第一医院妇产科）
Physics Driven Domain Specific Transporter Framework with Attention Mechanism for Ultrasound Imaging
Indian Institute of Technology Palakkad（印度理工学院帕拉卡德分校）；University of Alberta（阿尔伯塔大学）；Hospital Universitario Puerta de Hierro（铁门大学医院）；Government Medical College Thiruvananthapuram（特里凡得琅政府医学院）；Sree Chitra Tirunal Institute for Medical Sciences & Technology（斯里奇特拉蒂鲁纳尔医学科学与技术研究所）
Cross-Modal Ultrasound-MRI Learning for Fetal Brain Ventricular Volumetry and Abnormality Screening
Harvard Medical School（哈佛医学院）；Shenzhen University（深圳大学）；Centre for Artificial Intelligence and Robotics, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences（中国科学院香港创新研究院人工智能与机器人中心）；School of Artificial Intelligence, Shenzhen University（深圳大学人工智能学院）；School of Biomedical Engineering and Informatics, Nanjing Medical University（南京医科大学生物医学工程与信息学院）
A Chain-of-thought Reasoning Breast Ultrasound Dataset Covering All Histopathology Categories
Peking University（北京大学）；Peking Union Medical College Hospital（北京大学人民医院）；Peking University Cancer Hospital & Institute（北京大学肿瘤医院）；National Cancer Center / National Clinical Research Center for Cancer / Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College（中国医学科学院国家癌症中心/国家癌症临床科研中心/癌症医院）；Shenzhen Maternity & Child Health Care Hospital（深圳妇幼保健医院）；Xi’an Jiaotong University（西安交通大学）；Yizhun Medical AI Co., Ltd（亿众医疗人工智能有限公司）
Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning
Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiaotong University（上海交通大学医学院附属上海儿童医学中心）；Minhang District Centers for Disease Control and Prevention（闵行区疾病预防控制中心）；Xi’an Jiaotong-Liverpool University（西交利物浦大学）；East China Normal University（华东师范大学）；University of Shanghai for Science and Technology（上海理工大学）
CACTUSS: Common Anatomical CT-US Space for US examinations
Technical University of Munich（慕尼黑工业大学）；Sharif University of Technology（谢里夫理工大学）；Klinikum rechts der Isar（慕尼黑 Rechts der Isar 医院）；John Hopkins University（约翰·霍普金斯大学）
Lesion classification by model-based feature extraction: A differential affine invariant model of soft tissue elasticity
Stony Brook University（石溪大学）；City University of New York at CSI（纽约市立大学斯塔滕岛学院）；Southern Medical University（南方医科大学）；University of Texas Southwestern Medical Centre（德克萨斯大学西南医学中心）；The Fourth Medical University（第四医科大学）；University of Wisconsin（威斯康星大学）
