4 papers
Deep Learning-based Intelligent Diagnosis of Congenital Uterine Anomalies in 3D Ultrasound
Yueyue Xu, Yuhao Huang, Jiaxiao Deng +11
Objective: To develop an intelligent framework, termed CUA-Net, for the automated classification of congenital uterine anomalies (CUA) without requiring coronal plane reconstructio…
Improving O-RADS Risk Stratification from Ultrasound Reports: A Comparative Evaluation of Hybrid versus End-to-End LLM Reasoning Strategies
Xiaotong Tan, Chunli Qiu, Xin Liu +11
Background: Automating clinical guideline-based decision-making with large language models (LLMs) remains challenging because of reliability, hallucination, and limited interpretab…
Flip Learning: Weakly Supervised Erase to Segment Nodules in Breast Ultrasound
Yuhao Huang, Ao Chang, Haoran Dou +8
Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and treatment planning. Therefore, d…
Thyroid ultrasound diagnosis improvement via multi-view self-supervised learning and two-stage pre-training
Jian Wang, Xin Yang, Xiaohong Jia +9
Thyroid nodule classification and segmentation in ultrasound images are crucial for computer-aided diagnosis; however, they face limitations owing to insufficient labeled data. In…