578 citations · 1.7k across the 36 of their papers we have counts for
37 papers
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…
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…
Non-rigid Point Cloud Registration for Middle Ear Diagnostics with Endoscopic Optical Coherence Tomography
Peng Liu, Jonas Golde, Joseph Morgenstern +7
Purpose: Middle ear infection is the most prevalent inflammatory disease, especially among the pediatric population. Current diagnostic methods are subjective and depend on visual…
Why is the winner the best?
Matthias Eisenmann, Annika Reinke, Vivienn Weru +122
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…
Objective Surgical Skills Assessment and Tool Localization: Results from the MICCAI 2021 SimSurgSkill Challenge
Aneeq Zia, Kiran Bhattacharyya, Xi Liu +12
Timely and effective feedback within surgical training plays a critical role in developing the skills required to perform safe and efficient surgery. Feedback from expert surgeons,…
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…
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…
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…
Surgical Visual Domain Adaptation: Results from the MICCAI 2020 SurgVisDom Challenge
Aneeq Zia, Kiran Bhattacharyya, Xi Liu +10
Surgical data science is revolutionizing minimally invasive surgery by enabling context-aware applications. However, many challenges exist around surgical data (and health data, mo…
Stereo Correspondence and Reconstruction of Endoscopic Data Challenge
Max Allan, Jonathan Mcleod, Congcong Wang +21
The stereo correspondence and reconstruction of endoscopic data sub-challenge was organized during the Endovis challenge at MICCAI 2019 in Shenzhen, China. The task was to perform…
SERV-CT: A disparity dataset from CT for validation of endoscopic 3D reconstruction
P. J. "Eddie'' Edwards, Dimitris Psychogyios, Stefanie Speidel +2
In computer vision, reference datasets have been highly successful in promoting algorithmic development in stereo reconstruction. Surgical scenes gives rise to specific problems, i…
Surgical Data Science -- from Concepts toward Clinical Translation
Lena Maier-Hein, Matthias Eisenmann, Duygu Sarikaya +47
Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a…
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…
Non-Rigid Volume to Surface Registration using a Data-Driven Biomechanical Model
Micha Pfeiffer, Carina Riediger, Stefan Leger +5
Non-rigid registration is a key component in soft-tissue navigation. We focus on laparoscopic liver surgery, where we register the organ model obtained from a preoperative CT scan…
Heidelberg Colorectal Data Set for Surgical Data Science in the Sensor Operating Room
Lena Maier-Hein, Martin Wagner, Tobias Ross +30
Image-based tracking of medical instruments is an integral part of surgical data science applications. Previous research has addressed the tasks of detecting, segmenting and tracki…
Robust Medical Instrument Segmentation Challenge 2019
Tobias Ross, Annika Reinke, Peter M. Full +47
Intraoperative tracking of laparoscopic instruments is often a prerequisite for computer and robotic-assisted interventions. While numerous methods for detecting, segmenting and tr…
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…
2018 Robotic Scene Segmentation Challenge
Max Allan, Satoshi Kondo, Sebastian Bodenstedt +38
In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward ki…
Using 3D Convolutional Neural Networks to Learn Spatiotemporal Features for Automatic Surgical Gesture Recognition in Video
Isabel Funke, Sebastian Bodenstedt, Florian Oehme +3
Automatically recognizing surgical gestures is a crucial step towards a thorough understanding of surgical skill. Possible areas of application include automatic skill assessment,…
Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation
Micha Pfeiffer, Isabel Funke, Maria R. Robu +12
In the medical domain, the lack of large training data sets and benchmarks is often a limiting factor for training deep neural networks. In contrast to expensive manual labeling, c…
Learning Soft Tissue Behavior of Organs for Surgical Navigation with Convolutional Neural Networks
Micha Pfeiffer, Carina Riediger, Jürgen Weitz +1
Purpose: In surgical navigation, pre-operative organ models are presented to surgeons during the intervention to help them in efficiently finding their target. In the case of soft…
Video-based surgical skill assessment using 3D convolutional neural networks
Isabel Funke, Sören Torge Mees, Jürgen Weitz +1
Purpose: A profound education of novice surgeons is crucial to ensure that surgical interventions are effective and safe. One important aspect is the teaching of technical skills f…