output
20162026
most citedSurgical Data Science: Enabling Next-Generation Surgery

578 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2022Show all

7 papers · 1 filter

cs.CV2022★ 1 cited

Latent Graph Representations for Critical View of Safety Assessment

Aditya Murali, Deepak Alapatt, Pietro Mascagni +5

Assessing the critical view of safety in laparoscopic cholecystectomy requires accurate identification and localization of key anatomical structures, reasoning about their geometri…

cs.CV2022★ 38 cited

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…

cs.CV2022★ 469 cited

Metrics reloaded: Recommendations for image analysis validation

Lena Maier-Hein, Annika Reinke, Patrick Godau +71

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…

cs.CV2022★ 12 cited

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…

cs.CV2022★ 78 cited

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…

cs.CV2022★ 71 cited

Federated Cycling (FedCy): Semi-supervised Federated Learning of Surgical Phases

Hasan Kassem, Deepak Alapatt, Pietro Mascagni +3

Recent advancements in deep learning methods bring computer-assistance a step closer to fulfilling promises of safer surgical procedures. However, the generalizability of such meth…

eess.IV2022★ 11 cited

Live Laparoscopic Video Retrieval with Compressed Uncertainty

Tong Yu, Pietro Mascagni, Juan Verde +3

Searching through large volumes of medical data to retrieve relevant information is a challenging yet crucial task for clinical care. However the primitive and most common approach…