4 citations · 5 across the 7 of their papers we have counts for
8 papers
HeiCo-FOCUS: A Clinically Grounded Dataset for Long-Context Video Understanding
Leon Mayer, Lucas Luttner, Patrick Godau +42
Recent advances in Vision-Language Models (VLMs) have led to rapid progress in video understanding across a wide range of benchmark tasks. However, existing evaluations largely foc…
Training-free Temporal Object Tracking in Surgical Videos
Subhadeep Koley, Abdolrahim Kadkhodamohammadi, Santiago Barbarisi +2
Purpose: In this paper, we present a novel approach for online object tracking in laparoscopic cholecystectomy (LC) surgical videos, targeting localisation and tracking of critical…
Confidence-aware Monocular Depth Estimation for Minimally Invasive Surgery
Muhammad Asad, Emanuele Colleoni, Pritesh Mehta +7
Purpose: Monocular depth estimation (MDE) is vital for scene understanding in minimally invasive surgery (MIS). However, endoscopic video sequences are often contaminated by smoke,…
Graph Neural Networks for Surgical Scene Segmentation
Yihan Li, Nikhil Churamani, Maria Robu +2
Purpose: Accurate identification of hepatocystic anatomy is critical to preventing surgical complications during laparoscopic cholecystectomy. Deep learning models often struggle w…
Current validation practice undermines surgical AI development
Annika Reinke, Ziying O. Li, Minu D. Tizabi +98
Surgical data science (SDS) is rapidly advancing, yet clinical adoption of artificial intelligence (AI) in surgery remains limited, with inadequate validation as an important contr…
Zero-shot Monocular Metric Depth for Endoscopic Images
Nicolas Toussaint, Emanuele Colleoni, Ricardo Sanchez-Matilla +5
Monocular relative and metric depth estimation has seen a tremendous boost in the last few years due to the sharp advancements in foundation models and in particular transformer ba…
Temporal Cluster Assignment for Efficient Real-Time Video Segmentation
Ka-Wai Yung, Felix J. S. Bragman, Jialang Xu +3
Vision Transformers have substantially advanced the capabilities of segmentation models across both image and video domains. Among them, the Swin Transformer stands out for its abi…
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…