14 citations · 31 across the 17 of their papers we have counts for
17 papers
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…
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…
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…
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…
Dual Invariance Self-training for Reliable Semi-supervised Surgical Phase Recognition
Sahar Nasirihaghighi, Negin Ghamsarian, Raphael Sznitman +1
Accurate surgical phase recognition is crucial for advancing computer-assisted interventions, yet the scarcity of labeled data hinders training reliable deep learning models. Semi-…
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…
Deep-Learning-Assisted Analysis of Cataract Surgery Videos
Negin Ghamsarian
Following the technological advancements in medicine, the operation rooms are evolving into intelligent environments. The context-aware systems (CAS) can comprehensively interpret…
DeepPyramid+: Medical Image Segmentation using Pyramid View Fusion and Deformable Pyramid Reception
Negin Ghamsarian, Sebastian Wolf, Martin Zinkernagel +2
Semantic Segmentation plays a pivotal role in many applications related to medical image and video analysis. However, designing a neural network architecture for medical image and…
Predicting Postoperative Intraocular Lens Dislocation in Cataract Surgery via Deep Learning
Negin Ghamsarian, Doris Putzgruber-Adamitsch, Stephanie Sarny +3
A critical yet unpredictable complication following cataract surgery is intraocular lens dislocation. Postoperative stability is imperative, as even a tiny decentration of multifoc…
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…
Domain Adaptation for Medical Image Segmentation using Transformation-Invariant Self-Training
Negin Ghamsarian, Javier Gamazo Tejero, Pablo Márquez Neila +4
Models capable of leveraging unlabelled data are crucial in overcoming large distribution gaps between the acquired datasets across different imaging devices and configurations. In…
DeepPyramid: Enabling Pyramid View and Deformable Pyramid Reception for Semantic Segmentation in Cataract Surgery Videos
Negin Ghamsarian, Mario Taschwer, Raphael Sznitman +1
Semantic segmentation in cataract surgery has a wide range of applications contributing to surgical outcome enhancement and clinical risk reduction. However, the varying issues in…
ReCal-Net: Joint Region-Channel-Wise Calibrated Network for Semantic Segmentation in Cataract Surgery Videos
Negin Ghamsarian, Mario Taschwer, Doris Putzgruber-Adamitsch +3
Semantic segmentation in surgical videos is a prerequisite for a broad range of applications towards improving surgical outcomes and surgical video analysis. However, semantic segm…
DeepPyram: Enabling Pyramid View and Deformable Pyramid Reception for Semantic Segmentation in Cataract Surgery Videos
Negin Ghamsarian, Mario Taschwer, klaus Schoeffmann
Semantic segmentation in cataract surgery has a wide range of applications contributing to surgical outcome enhancement and clinical risk reduction. However, the varying issues in…
LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos
Negin Ghamsarian, Mario Taschwer, Doris Putzgruber-Adamitsch +3
A critical complication after cataract surgery is the dislocation of the lens implant leading to vision deterioration and eye trauma. In order to reduce the risk of this complicati…
Relevance Detection in Cataract Surgery Videos by Spatio-Temporal Action Localization
Negin Ghamsarian, Mario Taschwer, Doris Putzgruber-Adamitsch +2
In cataract surgery, the operation is performed with the help of a microscope. Since the microscope enables watching real-time surgery by up to two people only, a major part of sur…