176 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of AugsburgDE5 papers
- Ludwig-Maximilians-Universität MünchenDE4 papers
- Technical University of MunichDE4 papers
- Charité - Universitätsmedizin BerlinDE3 papers
- German Cancer Research CenterDE3 papers
- Imperial College LondonGB3 papers
- Munich Center for Machine Learning3 papers
- TUM KlinikumDE3 papers
- University Medical Center FreiburgDE3 papers
- University of FreiburgDE3 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE2 papers
- Heidelberg UniversityDE2 papers
14 papers
Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges
Lasse Hansen, Wiebke Heyer, Christoph Großbröhmer +51
Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the…
Learning dissection trajectories from expert surgical videos via imitation learning with equivariant diffusion
Hongyu Wang, Yonghao Long, Yueyao Chen +6
Endoscopic Submucosal Dissection (ESD) is a well-established technique for removing epithelial lesions. Predicting dissection trajectories in ESD videos offers significant potentia…
Sustained Vowels for Pre- vs Post-Treatment COPD Classification
Andreas Triantafyllopoulos, Anton Batliner, Wolfgang Mayr +6
Chronic obstructive pulmonary disease (COPD) is a serious inflammatory lung disease affecting millions of people around the world. Due to an obstructed airflow from the lungs, it a…
MRSegmentator: Multi-Modality Segmentation of 40 Classes in MRI and CT
Hartmut Häntze, Lina Xu, Christian J. Mertens +29
Purpose: To develop and evaluate a deep learning model for multi-organ segmentation of MRI scans. Materials and Methods: The model was trained on 1,200 manually annotated 3D axial…
SPINEPS -- Automatic Whole Spine Segmentation of T2-weighted MR images using a Two-Phase Approach to Multi-class Semantic and Instance Segmentation
Hendrik Möller, Robert Graf, Joachim Schmitt +16
Purpose. To present SPINEPS, an open-source deep learning approach for semantic and instance segmentation of 14 spinal structures (ten vertebra substructures, intervertebral discs,…
To tweak or not to tweak. How exploiting flexibilities in gene set analysis leads to over-optimism
Milena Wünsch, Christina Sauer, Moritz Herrmann +2
Gene set analysis, a popular approach for analysing high-throughput gene expression data, aims to identify sets of genes that show enriched expression patterns between two conditio…
Addressing researcher degrees of freedom through minP adjustment
Maximilian M Mandl, Andrea S Becker-Pennrich, Ludwig C Hinske +2
When different researchers study the same research question using the same dataset they may obtain different and potentially even conflicting results. This is because there is ofte…
Gradient and Uncertainty Enhanced Sequential Sampling for Global Fit
Sven Lämmle, Can Bogoclu, Kevin Cremanns +1
Surrogate models based on machine learning methods have become an important part of modern engineering to replace costly computer simulations. The data used for creating a surrogat…
From RNA sequencing measurements to the final results: a practical guide to navigating the choices and uncertainties of gene set analysis
Milena Wünsch, Christina Sauer, Patrick Callahan +2
Gene set analysis, a popular approach for analyzing high-throughput gene expression data, aims to identify sets of related genes that show significantly enriched or depleted expres…
Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma
Tirtha Chanda, Katja Hauser, Sarah Hobelsberger +32
Although artificial intelligence (AI) systems have been shown to improve the accuracy of initial melanoma diagnosis, the lack of transparency in how these systems identify melanoma…
Distinguishing between pre- and post-treatment in the speech of patients with chronic obstructive pulmonary disease
Andreas Triantafyllopoulos, Markus Fendler, Anton Batliner +4
Chronic obstructive pulmonary disease (COPD) causes lung inflammation and airflow blockage leading to a variety of respiratory symptoms; it is also a leading cause of death and aff…
Learning Visual Representations with Optimum-Path Forest and its Applications to Barrett's Esophagus and Adenocarcinoma Diagnosis
Luis A. de Souza, Luis C. S. Afonso, Alanna Ebigbo +5
In this work, we introduce the unsupervised Optimum-Path Forest (OPF) classifier for learning visual dictionaries in the context of Barrett's esophagus (BE) and automatic adenocarc…
The voice of COVID-19: Acoustic correlates of infection
Katrin D. Bartl-Pokorny, Florian B. Pokorny, Anton Batliner +8
COVID-19 is a global health crisis that has been affecting many aspects of our daily lives throughout the past year. The symptomatology of COVID-19 is heterogeneous with a severity…
Netboost: Boosting-supported network analysis improves high-dimensional omics prediction in acute myeloid leukemia and Huntington's disease
Pascal Schlosser, Jochen Knaus, Maximilian Schmutz +7
Background: State-of-the art selection methods fail to identify weak but cumulative effects of features found in many high-dimensional omics datasets. Nevertheless, these features…