578 citations · 1.8k across the 12 of their papers we have counts for
16 papers
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…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
Towards responsible research in digital technology for health care
Pierre Jannin
Digital technology is everywhere for the benefit of our daily and professional life. It strongly impacts our life and was crucial to maintain professional and social activities dur…
Common Limitations of Image Processing Metrics: A Picture Story
Annika Reinke, Minu D. Tizabi, Carole H. Sudre +90
While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are…
MIcro-Surgical Anastomose Workflow recognition challenge report
Arnaud Huaulmé, Duygu Sarikaya, Kévin Le Mut +12
The "MIcro-Surgical Anastomose Workflow recognition on training sessions" (MISAW) challenge provided a data set of 27 sequences of micro-surgical anastomosis on artificial blood ve…
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…
Towards Generalizable Surgical Activity Recognition Using Spatial Temporal Graph Convolutional Networks
Duygu Sarikaya, Pierre Jannin
Modeling and recognition of surgical activities poses an interesting research problem. Although a number of recent works studied automatic recognition of surgical activities, gener…
BIAS: Transparent reporting of biomedical image analysis challenges
Lena Maier-Hein, Annika Reinke, Michal Kozubek +11
The number of biomedical image analysis challenges organized per year is steadily increasing. These international competitions have the purpose of benchmarking algorithms on common…
Offline identification of surgical deviations in laparoscopic rectopexy
Arnaud Huaulmé, Pierre Jannin, Fabian Reche +3
Objective: A median of 14.4% of patient undergone at least one adverse event during surgery and a third of them are preventable. The occurrence of adverse events forces surgeons to…
Surgical Gesture Recognition with Optical Flow only
Duygu Sarikaya, Pierre Jannin
In this paper, we address the open research problem of surgical gesture recognition using motion cues from video data only. We adapt Optical flow ConvNets initially proposed by Sim…
Surgical Data Science: A Consensus Perspective
Lena Maier-Hein, Matthias Eisenmann, Carolin Feldmann +25
Surgical data science is a scientific discipline with the objective of improving the quality of interventional healthcare and its value through capturing, organization, analysis, a…
Why rankings of biomedical image analysis competitions should be interpreted with care
Lena Maier-Hein, Matthias Eisenmann, Annika Reinke +35
International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of c…
Analyzing Before Solving: Which Parameters Influence Low-Level Surgical Activity Recognition
Olga Dergachyova, Xavier Morandi, Pierre Jannin
Automatic low-level surgical activity recognition is today well-known technical bottleneck for smart and situation-aware assistance for the operating room of the future. Our study…
Knowledge transfer for surgical activity prediction
Olga Dergachyova, Xavier Morandi, Pierre Jannin
Lack of training data hinders automatic recognition and prediction of surgical activities necessary for situation-aware operating rooms. We propose using knowledge transfer to comp…
Surgical Data Science: Enabling Next-Generation Surgery
Lena Maier-Hein, Swaroop Vedula, Stefanie Speidel +22
This paper introduces Surgical Data Science as an emerging scientific discipline. Key perspectives are based on discussions during an intensive two-day international interactive wo…