4 papers · 1 filter
SAM-Fed: SAM-Guided Federated Semi-Supervised Learning for Medical Image Segmentation
Sahar Nasirihaghighi, Negin Ghamsarian, Yiping Li +3
Medical image segmentation is clinically important, yet data privacy and the cost of expert annotation limit the availability of labeled data. Federated semi-supervised learning (F…
WetCat: Enabling Automated Skill Assessment in Wet-Lab Cataract Surgery Videos
Negin Ghamsarian, Raphael Sznitman, Klaus Schoeffmann +1
To meet the growing demand for systematic surgical training, wet-lab environments have become indispensable platforms for hands-on practice in ophthalmology. Yet, traditional wet-l…
GynSurg: A Comprehensive Gynecology Laparoscopic Surgery Dataset
Sahar Nasirihaghighi, Negin Ghamsarian, Leonie Peschek +4
Recent advances in deep learning have transformed computer-assisted intervention and surgical video analysis, driving improvements not only in surgical training, intraoperative dec…
Feedback-Driven Pseudo-Label Reliability Assessment: Redefining Thresholding for Semi-Supervised Semantic Segmentation
Negin Ghamsarian, Sahar Nasirihaghighi, Klaus Schoeffmann +1
Semi-supervised learning leverages unlabeled data to enhance model performance, addressing the limitations of fully supervised approaches. Among its strategies, pseudo-supervision…