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
4 papers · 1 filter
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…