118 citations · 250 across the 15 of their papers we have counts for
16 papers
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…
Learning from Single Timestamps: Complexity Estimation in Laparoscopic Cholecystectomy
Dimitrios Anastasiou, Santiago Barbarisi, Lucy Culshaw +4
Purpose: Accurate assessment of surgical complexity is essential in Laparoscopic Cholecystectomy (LC), where severe inflammation is associated with longer operative times and incre…
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…
A spatio-temporal network for video semantic segmentation in surgical videos
Maria Grammatikopoulou, Ricardo Sanchez-Matilla, Felix Bragman +5
Semantic segmentation in surgical videos has applications in intra-operative guidance, post-operative analytics and surgical education. Segmentation models need to provide accurate…
Self-Knowledge Distillation for Surgical Phase Recognition
Jinglu Zhang, Santiago Barbarisi, Abdolrahim Kadkhodamohammadi +2
Purpose: Advances in surgical phase recognition are generally led by training deeper networks. Rather than going further with a more complex solution, we believe that current model…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
CholecTriplet2021: A benchmark challenge for surgical action triplet recognition
Chinedu Innocent Nwoye, Deepak Alapatt, Tong Yu +59
Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works…
2020 CATARACTS Semantic Segmentation Challenge
Imanol Luengo, Maria Grammatikopoulou, Rahim Mohammadi +37
Surgical scene segmentation is essential for anatomy and instrument localization which can be further used to assess tissue-instrument interactions during a surgical procedure. In…
2018 Robotic Scene Segmentation Challenge
Max Allan, Satoshi Kondo, Sebastian Bodenstedt +38
In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward ki…
CaDIS: Cataract Dataset for Image Segmentation
Maria Grammatikopoulou, Evangello Flouty, Abdolrahim Kadkhodamohammadi +5
Video feedback provides a wealth of information about surgical procedures and is the main sensory cue for surgeons. Scene understanding is crucial to computer assisted intervention…
DeepPhase: Surgical Phase Recognition in CATARACTS Videos
Odysseas Zisimopoulos, Evangello Flouty, Imanol Luengo +4
Automated surgical workflow analysis and understanding can assist surgeons to standardize procedures and enhance post-surgical assessment and indexing, as well as, interventional m…
Hierarchical Piecewise-Constant Super-regions
Imanol Luengo, Mark Basham, Andrew P. French
Recent applications in computer vision have come to heavily rely on superpixel over-segmentation as a pre-processing step for higher level vision tasks, such as object recognition,…