2 citations · 5 across the 14 of their papers we have counts for
14 papers
ExpOS: Explainable Open-Surgery Skills Assessment Using 3D Hand Reconstruction
Roi Papo, Idan Smoller, Shlomi Laufer
Timely and transparent feedback is essential for effective surgical training, yet current assessment remains dependent on expert observation, limiting scalability and opportunities…
OSS: Open Suturing Skills Vision-Based Assessment Challenge 2024-2025
Hanna Hoffmann, Setareh Bady, Claas de Boer +54
Achieving high levels of surgical skill through effective training is essential for optimal patient outcomes. Automated, data-driven skill assessment holds significant potential to…
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…
RoHan: Robust Hand Detection in Operation Room
Roi Papo, Sapir Gershov, Tom Friedman +3
Hand-specific localization has garnered significant interest within the computer vision community. Although there are numerous datasets with hand annotations from various angles an…
Monocular pose estimation of articulated open surgery tools -- in the wild
Robert Spektor, Tom Friedman, Itay Or +2
This work presents a framework for monocular 6D pose estimation of surgical instruments in open surgery, addressing challenges such as object articulations, specularity, occlusions…
Robust Surgical Phase Recognition From Annotation Efficient Supervision
Or Rubin, Shlomi Laufer
Surgical phase recognition is a key task in computer-assisted surgery, aiming to automatically identify and categorize the different phases within a surgical procedure. Despite sub…
CuVLER: Enhanced Unsupervised Object Discoveries through Exhaustive Self-Supervised Transformers
Shahaf Arica, Or Rubin, Sapir Gershov +1
In this paper, we introduce VoteCut, an innovative method for unsupervised object discovery that leverages feature representations from multiple self-supervised models. VoteCut emp…
Depth Over RGB: Automatic Evaluation of Open Surgery Skills Using Depth Camera
Ido Zuckerman, Nicole Werner, Jonathan Kouchly +4
Purpose: In this paper, we present a novel approach to the automatic evaluation of open surgery skills using depth cameras. This work is intended to show that depth cameras achieve…
SFGANS Self-supervised Future Generator for human ActioN Segmentation
Or Berman, Adam Goldbraikh, Shlomi Laufer
The ability to locate and classify action segments in long untrimmed video is of particular interest to many applications such as autonomous cars, robotics and healthcare applicati…
MS-TCRNet: Multi-Stage Temporal Convolutional Recurrent Networks for Action Segmentation Using Sensor-Augmented Kinematics
Adam Goldbraikh, Omer Shubi, Or Rubin +2
Action segmentation is a challenging task in high-level process analysis, typically performed on video or kinematic data obtained from various sensors. This work presents two contr…
Using Hand Pose Estimation To Automate Open Surgery Training Feedback
Eddie Bkheet, Anne-Lise D'Angelo, Adam Goldbraikh +1
Purpose: This research aims to facilitate the use of state-of-the-art computer vision algorithms for the automated training of surgeons and the analysis of surgical footage. By est…
Bounded Future MS-TCN++ for surgical gesture recognition
Adam Goldbraikh, Netanell Avisdris, Carla M. Pugh +1
In recent times there is a growing development of video based applications for surgical purposes. Part of these applications can work offline after the end of the procedure, other…
Open surgery tool classification and hand utilization using a multi-camera system
Kristina Basiev, Adam Goldbraikh, Carla M Pugh +1
Purpose: The goal of this work is to use multi-camera video to classify open surgery tools as well as identify which tool is held in each hand. Multi-camera systems help prevent oc…
Video-based fully automatic assessment of open surgery suturing skills
Adam Goldbraikh, Anne-Lise D'Angelo, Carla M. Pugh +1
The goal of this study was to develop new reliable open surgery suturing simulation system for training medical students in situation where resources are limited or in the domestic…