14 citations · 14 across the 8 of their papers we have counts for
6 papers · 1 filter
Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma by Integrating Multimodal Ultrasound and Clinical Data: A Multicenter Study
Jun Cheng, Yuanyuan Kong, Qing Huang +9
Background: Microvascular invasion (MVI) predicts recurrence and survival in hepatocellular carcinoma (HCC) but requires postoperative histopathology for diagnosis. We developed an…
Subtyping Breast Lesions via Generative Augmentation based Long-tailed Recognition in Ultrasound
Shijing Chen, Xinrui Zhou, Yuhao Wang +4
Accurate identification of breast lesion subtypes can facilitate personalized treatment and interventions. Ultrasound (US), as a safe and accessible imaging modality, is extensivel…
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…
EM-Net: Efficient Channel and Frequency Learning with Mamba for 3D Medical Image Segmentation
Ao Chang, Jiajun Zeng, Ruobing Huang +1
Convolutional neural networks have primarily led 3D medical image segmentation but may be limited by small receptive fields. Transformer models excel in capturing global relationsh…
Ctrl-GenAug: Controllable Generative Augmentation for Medical Sequence Classification
Xinrui Zhou, Yuhao Huang, Haoran Dou +13
In the medical field, the limited availability of large-scale datasets and labor-intensive annotation processes hinder the performance of deep models. Diffusion-based generative au…
TriAug: Out-of-Distribution Detection for Imbalanced Breast Lesion in Ultrasound
Yinyu Ye, Shijing Chen, Dong Ni +1
Different diseases, such as histological subtypes of breast lesions, have severely varying incidence rates. Even trained with substantial amount of in-distribution (ID) data, model…