71 citations · 94 across the 4 of their papers we have counts for
5 papers
Uncertainty as a Proxy for Semantic Correctness in Diffusion-Based Medical Image Synthesis
Yuxuan Ou, Konstantinos Kamnitsas, OxAAA Study +3
Diffusion models can synthesise contrast-enhanced CT (CECT) from non-contrast CT (NCCT), avoiding contrast administration and its environmental and patient-access costs. However, v…
GEN-Guard: Correcting Generalization Failures for Deployable Federated Surgical AI
Julia Alekseenko, Pietro Mascagni, AI4SafeChole Consortium +1
Federated Learning (FL) in surgical video AI enables collaborative model training without sharing sensitive data. However, standard evaluation practices - selecting the "best" glob…
Jumpstarting Surgical Computer Vision
Deepak Alapatt, Aditya Murali, Vinkle Srivastav +3
Consensus amongst researchers and industry points to a lack of large, representative annotated datasets as the biggest obstacle to progress in the field of surgical data science. A…
Preserving Privacy in Surgical Video Analysis Using Artificial Intelligence: A Deep Learning Classifier to Identify Out-of-Body Scenes in Endoscopic Videos
Joël L. Lavanchy, Armine Vardazaryan, Pietro Mascagni +3
Objective: To develop and validate a deep learning model for the identification of out-of-body images in endoscopic videos. Background: Surgical video analysis facilitates educatio…
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…