502 citations · 504 across the 6 of their papers we have counts for
7 papers
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…
PE-MED: Prompt Enhancement for Interactive Medical Image Segmentation
Ao Chang, Xing Tao, Xin Yang +5
Interactive medical image segmentation refers to the accurate segmentation of the target of interest through interaction (e.g., click) between the user and the image. It has been w…
OnUVS: Online Feature Decoupling Framework for High-Fidelity Ultrasound Video Synthesis
Han Zhou, Dong Ni, Ao Chang +10
Ultrasound (US) imaging is indispensable in clinical practice. To diagnose certain diseases, sonographers must observe corresponding dynamic anatomic structures to gather comprehen…
Segment Anything Model for Medical Images?
Yuhao Huang, Xin Yang, Lian Liu +16
The Segment Anything Model (SAM) is the first foundation model for general image segmentation. It has achieved impressive results on various natural image segmentation tasks. Howev…