4 citations · 6 across the 3 of their papers we have counts for
4 papers
ZAGNet: Zone-Aware Graph Aggregation Network for Patient-Level Lung Ultrasound Diagnosis
Li Chen, Shubham Patil, Rashid Al Mukaddim +3
Patient-level lung ultrasound (LUS) diagnosis requires integrating findings acquired across multiple anatomical zones, yet clinical examinations frequently involve variable and inc…
Ultrasound Image Synthesis Using Generative AI for Lung Ultrasound Detection
Yu-Cheng Chou, Gary Y. Li, Li Chen +15
Developing reliable healthcare AI models requires training with representative and diverse data. In imbalanced datasets, model performance tends to plateau on the more prevalent cl…
SAM Fewshot Finetuning for Anatomical Segmentation in Medical Images
Weiyi Xie, Nathalie Willems, Shubham Patil +2
We propose a straightforward yet highly effective few-shot fine-tuning strategy for adapting the Segment Anything (SAM) to anatomical segmentation tasks in medical images. Our nove…
Contrastive Self-Supervised Learning for Spatio-Temporal Analysis of Lung Ultrasound Videos
Li Chen, Jonathan Rubin, Jiahong Ouyang +24
Self-supervised learning (SSL) methods have shown promise for medical imaging applications by learning meaningful visual representations, even when the amount of labeled data is li…