3 citations · 3 across the 3 of their papers we have counts for
5 papers
How can we learn (more) from challenges? A statistical approach to driving future algorithm development
Tobias Roß, Pierangela Bruno, Annika Reinke +12
Challenges have become the state-of-the-art approach to benchmark image analysis algorithms in a comparative manner. While the validation on identical data sets was a great step fo…
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…
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…
Exploiting the potential of unlabeled endoscopic video data with self-supervised learning
Tobias Ross, David Zimmerer, Anant Vemuri +12
Surgical data science is a new research field that aims to observe all aspects of the patient treatment process in order to provide the right assistance at the right time. Due to t…