Area of research
Surgery · Biomedical Engineering
Research interest
Research interests include Surgical Simulation and Training, Soft Robotics and Applications, Anatomy and Medical Technology, and Robotics and Sensor-Based Localization.
Surgical workflow analysis for Surgomics and context-aware assistance in robot-assisted minimally invasive esophagectomy (RAMIE): a retrospective, single-arm, multicenter annotation and machine learning study
AutoFRS: an externally validated, annotation-free approach to computational preoperative complication risk stratification in pancreatic surgery – an experimental study
AIxSuture: vision-based assessment of open suturing skills
The Dresden in vivo OCT dataset for automatic middle ear segmentation
A surgical activity model of laparoscopic cholecystectomy for co-operation with collaborative robots
Aliado - A design concept of AI for decision support in oncological liver surgery
One model to use them all: training a segmentation model with complementary datasets
Importance of the Data in the Surgical Environment
Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark
CholecTriplet2021: A benchmark challenge for surgical action triplet recognition
Artificial Intelligence for context-aware surgical guidance in complex robot-assisted oncological procedures: An exploratory feasibility study
Anatomy segmentation in laparoscopic surgery: comparison of machine learning and human expertise – an experimental study
Active learning for extracting surgomic features in robot-assisted minimally invasive esophagectomy: a prospective annotation study
Why is the Winner the Best?
Ensuring privacy protection in the era of big laparoscopic video data: development and validation of an inside outside discrimination algorithm (IODA)
Why is the winner the best?
Surgomics: personalized prediction of morbidity, mortality and long-term outcome in surgery using machine learning on multimodal data
The importance of machine learning in autonomous actions for surgical decision making
Biomedical image analysis competitions: The state of current participation practice
Artificial intelligence for decision support in surgical oncology - a systematic review
Artificial Intelligence for context-aware surgical guidance in complex robot-assisted oncological procedures: An exploratory feasibility study
Anatomy Segmentation in Laparoscopic Surgery: Comparison of Machine Learning and Human Expertise – An Experimental Study
Technische Innovationen und Blick in die Zukunft
„Cognition-Guided Surgery“ – computergestützte intelligente Assistenzsysteme für die onkologische Chirurgie
„Cognition-Guided Surgery“ – computergestützte intelligente Assistenzsysteme für die onkologische Chirurgie
Heidelberg colorectal data set for surgical data science in the sensor operating room
Endoscopic Vision Challenge 2021
Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge
Patch-based adaptive weighting with segmentation and scale (PAWSS) for visual tracking in surgical video
Generating Large Labeled Data Sets for Laparoscopic Image Processing Tasks Using Unpaired Image-to-Image Translation