210 citations · 599 across the 25 of their papers we have counts for
25 papers
SUREON: A Benchmark and Vision-Language-Model for Surgical Reasoning
Alejandra Perez, Anita Rau, Lee White +4
Surgeons don't just see -- they interpret. When an expert observes a surgical scene, they understand not only what instrument is being used, but why it was chosen, what risk it pos…
On the Role of Depth in Surgical Vision Foundation Models: An Empirical Study of RGB-D Pre-training
John J. Han, Adam Schmidt, Muhammad Abdullah Jamal +4
Vision foundation models (VFMs) have emerged as powerful tools for surgical scene understanding. However, current approaches predominantly rely on unimodal RGB pre-training, overlo…
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…
State-Change Learning for Prediction of Future Events in Endoscopic Videos
Saurav Sharma, Chinedu Innocent Nwoye, Didier Mutter +1
Surgical future prediction, driven by real-time AI analysis of surgical video, is critical for operating room safety and efficiency. It provides actionable insights into upcoming e…
SurgLaVi: Large-Scale Hierarchical Dataset for Surgical Vision-Language Representation Learning
Alejandra Perez, Chinedu Nwoye, Ramtin Raji Kermani +2
Vision-language pre-training (VLP) offers unique advantages for surgery by aligning language with surgical videos, enabling workflow understanding and transfer across tasks without…
Feature Mixing Approach for Detecting Intraoperative Adverse Events in Laparoscopic Roux-en-Y Gastric Bypass Surgery
Rupak Bose, Chinedu Innocent Nwoye, Jorge Lazo +2
Intraoperative adverse events (IAEs), such as bleeding or thermal injury, can lead to severe postoperative complications if undetected. However, their rarity results in highly imba…
CoSimGen: Controllable Diffusion Model for Simultaneous Image and Mask Generation
Rupak Bose, Chinedu Innocent Nwoye, Aditya Bhat +1
The acquisition of annotated datasets with paired images and segmentation masks is a critical challenge in domains such as medical imaging, remote sensing, and computer vision. Man…
SimGen: A Diffusion-Based Framework for Simultaneous Surgical Image and Segmentation Mask Generation
Aditya Bhat, Rupak Bose, Chinedu Innocent Nwoye +1
Acquiring and annotating surgical data is often resource-intensive, ethical constraining, and requiring significant expert involvement. While generative AI models like text-to-imag…
Surgical Text-to-Image Generation
Chinedu Innocent Nwoye, Rupak Bose, Kareem Elgohary +5
Acquiring surgical data for research and development is significantly hindered by high annotation costs and practical and ethical constraints. Utilizing synthetically generated ima…
SurgiTrack: Fine-Grained Multi-Class Multi-Tool Tracking in Surgical Videos
Chinedu Innocent Nwoye, Nicolas Padoy
Accurate tool tracking is essential for the success of computer-assisted intervention. Previous efforts often modeled tool trajectories rigidly, overlooking the dynamic nature of s…
CholecTrack20: A Multi-Perspective Tracking Dataset for Surgical Tools
Chinedu Innocent Nwoye, Kareem Elgohary, Anvita Srinivas +3
Tool tracking in surgical videos is essential for advancing computer-assisted interventions, such as skill assessment, safety zone estimation, and human-machine collaboration. Howe…
Surgical Action Triplet Detection by Mixed Supervised Learning of Instrument-Tissue Interactions
Saurav Sharma, Chinedu Innocent Nwoye, Didier Mutter +1
Surgical action triplets describe instrument-tissue interactions as (instrument, verb, target) combinations, thereby supporting a detailed analysis of surgical scene activities and…
Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025
Aneeq Zia, Max Berniker, Rogerio Garcia Nespolo +153
Robotic assisted (RA) surgery promises to transform surgical intervention. Intuitive Surgical is committed to fostering these changes and the machine learning models and algorithms…
Self-distillation for surgical action recognition
Amine Yamlahi, Thuy Nuong Tran, Patrick Godau +9
Surgical scene understanding is a key prerequisite for contextaware decision support in the operating room. While deep learning-based approaches have already reached or even surpas…
CholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection
Chinedu Innocent Nwoye, Tong Yu, Saurav Sharma +46
Formalizing surgical activities as triplets of the used instruments, actions performed, and target anatomies is becoming a gold standard approach for surgical activity modeling. Th…
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…
Rendezvous in Time: An Attention-based Temporal Fusion approach for Surgical Triplet Recognition
Saurav Sharma, Chinedu Innocent Nwoye, Didier Mutter +1
One of the recent advances in surgical AI is the recognition of surgical activities as triplets of (instrument, verb, target). Albeit providing detailed information for computer-as…
Dissecting Self-Supervised Learning Methods for Surgical Computer Vision
Sanat Ramesh, Vinkle Srivastav, Deepak Alapatt +10
The field of surgical computer vision has undergone considerable breakthroughs in recent years with the rising popularity of deep neural network-based methods. However, standard fu…
Data Splits and Metrics for Method Benchmarking on Surgical Action Triplet Datasets
Chinedu Innocent Nwoye, Nicolas Padoy
In addition to generating data and annotations, devising sensible data splitting strategies and evaluation metrics is essential for the creation of a benchmark dataset. This practi…
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…
Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark
Martin Wagner, Beat-Peter Müller-Stich, Anna Kisilenko +38
PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the…
Rendezvous: Attention Mechanisms for the Recognition of Surgical Action Triplets in Endoscopic Videos
Chinedu Innocent Nwoye, Tong Yu, Cristians Gonzalez +5
Out of all existing frameworks for surgical workflow analysis in endoscopic videos, action triplet recognition stands out as the only one aiming to provide truly fine-grained and c…
Recognition of Instrument-Tissue Interactions in Endoscopic Videos via Action Triplets
Chinedu Innocent Nwoye, Cristians Gonzalez, Tong Yu +4
Recognition of surgical activity is an essential component to develop context-aware decision support for the operating room. In this work, we tackle the recognition of fine-grained…