4.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National Center for Tumor DiseasesDE17 papers
- University Hospital Carl Gustav CarusDE12 papers
- Heidelberg UniversityDE11 papers
- German Cancer Research CenterDE10 papers
- Technische Universität DresdenDE8 papers
- University Hospital HeidelbergDE7 papers
- Helmholtz-Zentrum Dresden-RossendorfDE6 papers
- University College LondonGB6 papers
- Technical University of MunichDE4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Chinese University of Hong KongHK3 papers
- InsermFR3 papers
23 papers
Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge
Max Kirchner, Hanna Hoffmann, Alexander C. Jenke +16
Developing generalizable surgical AI requires multi-institutional data, yet privacy constraints preclude direct data sharing, making Federated Learning (FL) a natural candidate. It…
Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge
Tobias Rueckert, David Rauber, Raphaela Maerkl +58
Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minim…
From zero to figure hero. A checklist for designing scientific data visualizations
Helena Klara Jambor
Biological research spans scales and methodologies, generating complex data visualizations such as images, text, numbers, networks, and maps. With increasingly large and multimodal…
Image segmentation of treated and untreated tumor spheroids by Fully Convolutional Networks
Matthias Streller, Soňa Michlíková, Willy Ciecior +4
Multicellular tumor spheroids (MCTS) are advanced cell culture systems for assessing the impact of combinatorial radio(chemo)therapy. They exhibit therapeutically relevant in-vivo-…
Clinical Melanoma Diagnosis with Artificial Intelligence: Insights from a Prospective Multicenter Study
Lukas Heinlein, Roman C. Maron, Achim Hekler +27
Early detection of melanoma, a potentially lethal type of skin cancer with high prevalence worldwide, improves patient prognosis. In retrospective studies, artificial intelligence…
Generalized, sublethal damage-based mathematical approach for improved modeling of clonogenic survival curve flattening upon hyperthermia, radiotherapy, and beyond
Adriana M. De Mendoza, Soňa Michlíková, Paula S. Castro +4
Mathematical modeling can offer valuable insights into the behavior of biological systems upon treatment. Different mathematical models have been designed to predict the efficacy o…
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…
Using Multiple Dermoscopic Photographs of One Lesion Improves Melanoma Classification via Deep Learning: A Prognostic Diagnostic Accuracy Study
Achim Hekler, Roman C. Maron, Sarah Haggenmüller +28
Background: Convolutional neural network (CNN)-based melanoma classifiers face several challenges that limit their usefulness in clinical practice. Objective: To investigate the im…
Community-developed checklists for publishing images and image analysis
Christopher Schmied, Michael Nelson, Sergiy Avilov +51
Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. H…
Learning shape distributions from large databases of healthy organs: applications to zero-shot and few-shot abnormal pancreas detection
Rebeca Vétil, Clément Abi Nader, Alexandre Bône +4
We propose a scalable and data-driven approach to learn shape distributions from large databases of healthy organs. To do so, volumetric segmentation masks are embedded into a comm…
CholecTriplet2021: A benchmark challenge for surgical action triplet recognition
Chinedu Innocent Nwoye, Deepak Alapatt, Tong Yu +59
Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works…
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…
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…
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…
Domain specific cues improve robustness of deep learning based segmentation of ct volumes
Marie Kloenne, Sebastian Niehaus, Leonie Lampe +4
Machine Learning has considerably improved medical image analysis in the past years. Although data-driven approaches are intrinsically adaptive and thus, generic, they often do not…
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…
Assessing robustness of radiomic features by image perturbation
Alex Zwanenburg, Stefan Leger, Linda Agolli +4
Image features need to be robust against differences in positioning, acquisition and segmentation to ensure reproducibility. Radiomic models that only include robust features can b…
Temporal coherence-based self-supervised learning for laparoscopic workflow analysis
Isabel Funke, Alexander Jenke, Sören Torge Mees +3
In order to provide the right type of assistance at the right time, computer-assisted surgery systems need context awareness. To achieve this, methods for surgical workflow analysi…
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…
IMHOTEP - Virtual Reality Framework for Surgical Applications
Micha Pfeiffer, Hannes Kenngott, Anas Preukschas +4
Purpose: The data which is available to surgeons before, during and after surgery is steadily increasing in quantity as well as diversity. When planning a patient's treatment, this…
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…
Image biomarker standardisation initiative
Alex Zwanenburg, Stefan Leger, Martin Vallières +1
The image biomarker standardisation initiative (IBSI) is an independent international collaboration which works towards standardising the extraction of image biomarkers from acquir…