215 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Else Kröner Fresenius Center for Digital HealthDE9 papers
- Heidelberg UniversityDE5 papers
- National Center for Tumor DiseasesDE5 papers
- University Hospital HeidelbergDE5 papers
- RWTH Aachen UniversityDE4 papers
- University Hospital Carl Gustav CarusDE3 papers
- Stanford UniversityUS2 papers
- Technische Universität DresdenDE2 papers
- Universitätsklinikum AachenDE2 papers
- All India Institute of Medical SciencesIN1 paper
- Beijing Academy of Artificial IntelligenceCN1 paper
- Broad InstituteUS1 paper
6 papers · 1 filter
Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2
Gustav Müller-Franzes, Firas Khader, Robert Siepmann +4
MRI and CT are essential clinical cross-sectional imaging techniques for diagnosing complex conditions. However, large 3D datasets with annotations for deep learning are scarce. Wh…
Enhancing Network Initialization for Medical AI Models Using Large-Scale, Unlabeled Natural Images
Soroosh Tayebi Arasteh, Leo Misera, Jakob Nikolas Kather +2
Pre-training datasets, like ImageNet, have become the gold standard in medical image analysis. However, the emergence of self-supervised learning (SSL), which leverages unlabeled d…
The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions
Jun Ma, Ronald Xie, Shamini Ayyadhury +37
Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or req…
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…
Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers -- A multi-institutional evaluation
Gustav Müller-Franzes, Fritz Müller-Franzes, Luisa Huck +9
Accurate and automatic segmentation of fibroglandular tissue in breast MRI screening is essential for the quantification of breast density and background parenchymal enhancement. I…
Diffusion Probabilistic Models beat GANs on Medical Images
Gustav Müller-Franzes, Jan Moritz Niehues, Firas Khader +8
The success of Deep Learning applications critically depends on the quality and scale of the underlying training data. Generative adversarial networks (GANs) can generate arbitrary…