12 citations · 20 across the 11 of their papers we have counts for
8 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…
Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge
Tobias Rueckert, David Rauber, Raphaela Maerkl +58
Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minim…
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…
SemiVT-Surge: Semi-Supervised Video Transformer for Surgical Phase Recognition
Yiping Li, Ronald de Jong, Sahar Nasirihaghighi +8
Accurate surgical phase recognition is crucial for computer-assisted interventions and surgical video analysis. Annotating long surgical videos is labor-intensive, driving research…
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…
Cataract-1K: Cataract Surgery Dataset for Scene Segmentation, Phase Recognition, and Irregularity Detection
Negin Ghamsarian, Yosuf El-Shabrawi, Sahar Nasirihaghighi +5
In recent years, the landscape of computer-assisted interventions and post-operative surgical video analysis has been dramatically reshaped by deep-learning techniques, resulting i…
Event Recognition in Laparoscopic Gynecology Videos with Hybrid Transformers
Sahar Nasirihaghighi, Negin Ghamsarian, Heinrich Husslein +1
Analyzing laparoscopic surgery videos presents a complex and multifaceted challenge, with applications including surgical training, intra-operative surgical complication prediction…
Action Recognition in Video Recordings from Gynecologic Laparoscopy
Sahar Nasirihaghighi, Negin Ghamsarian, Daniela Stefanics +2
Action recognition is a prerequisite for many applications in laparoscopic video analysis including but not limited to surgical training, operation room planning, follow-up surgery…