21 citations · 47 across the 12 of their papers we have counts for
12 papers
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…
Data Augmentation for Surgical Scene Segmentation with Anatomy-Aware Diffusion Models
Danush Kumar Venkatesh, Dominik Rivoir, Micha Pfeiffer +2
In computer-assisted surgery, automatically recognizing anatomical organs is crucial for understanding the surgical scene and providing intraoperative assistance. While machine lea…
PitVis-2023 Challenge: Workflow Recognition in videos of Endoscopic Pituitary Surgery
Adrito Das, Danyal Z. Khan, Dimitrios Psychogyios +29
The field of computer vision applied to videos of minimally invasive surgery is ever-growing. Workflow recognition pertains to the automated recognition of various aspects of a sur…
SurgicaL-CD: Generating Surgical Images via Unpaired Image Translation with Latent Consistency Diffusion Models
Danush Kumar Venkatesh, Dominik Rivoir, Micha Pfeiffer +1
Computer-assisted surgery (CAS) systems are designed to assist surgeons during procedures, thereby reducing complications and enhancing patient care. Training machine learning mode…
Exploring Semantic Consistency in Unpaired Image Translation to Generate Data for Surgical Applications
Danush Kumar Venkatesh, Dominik Rivoir, Micha Pfeiffer +4
In surgical computer vision applications, obtaining labeled training data is challenging due to data-privacy concerns and the need for expert annotation. Unpaired image-to-image tr…
TUNeS: A Temporal U-Net with Self-Attention for Video-based Surgical Phase Recognition
Isabel Funke, Dominik Rivoir, Stefanie Krell +1
Objective: To enable context-aware computer assistance in the operating room of the future, cognitive systems need to understand automatically which surgical phase is being perform…
Metrics Matter in Surgical Phase Recognition
Isabel Funke, Dominik Rivoir, Stefanie Speidel
Surgical phase recognition is a basic component for different context-aware applications in computer- and robot-assisted surgery. In recent years, several methods for automatic sur…
On the Pitfalls of Batch Normalization for End-to-End Video Learning: A Study on Surgical Workflow Analysis
Dominik Rivoir, Isabel Funke, Stefanie Speidel
Batch Normalization's (BN) unique property of depending on other samples in a batch is known to cause problems in several tasks, including sequence modeling. Yet, BN-related issues…
Long-Term Temporally Consistent Unpaired Video Translation from Simulated Surgical 3D Data
Dominik Rivoir, Micha Pfeiffer, Reuben Docea +4
Research in unpaired video translation has mainly focused on short-term temporal consistency by conditioning on neighboring frames. However for transfer from simulated to photoreal…
Rethinking Anticipation Tasks: Uncertainty-aware Anticipation of Sparse Surgical Instrument Usage for Context-aware Assistance
Dominik Rivoir, Sebastian Bodenstedt, Isabel Funke +4
Intra-operative anticipation of instrument usage is a necessary component for context-aware assistance in surgery, e.g. for instrument preparation or semi-automation of robotic tas…
Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration
Dominik Rivoir, Sebastian Bodenstedt, Felix von Bechtolsheim +3
Estimating the remaining surgery duration (RSD) during surgical procedures can be useful for OR planning and anesthesia dose estimation. With the recent success of deep learning-ba…
Active Learning using Deep Bayesian Networks for Surgical Workflow Analysis
Sebastian Bodenstedt, Dominik Rivoir, Alexander Jenke +6
For many applications in the field of computer assisted surgery, such as providing the position of a tumor, specifying the most probable tool required next by the surgeon or determ…