11 papers
DSA-CycleGAN: A Domain Shift Aware CycleGAN for Robust Multi-Stain Glomeruli Segmentation
Zeeshan Nisar, Friedrich Feuerhake, Thomas Lampert
A key challenge in segmentation in digital histopathology is inter- and intra-stain variations as it reduces model performance. Labelling each stain is expensive and time-consuming…
Explainable histomorphology-based survival prediction of glioblastoma, IDH-wildtype
Jan-Philipp Redlich, Friedrich Feuerhake, Stefan Nikolin +12
Glioblastoma, IDH-wildtype (GBM-IDHwt) is the most common malignant brain tumor. While histomorphology is a crucial component of GBM-IDHwt diagnosis, it is not further considered f…
Tissue Classification and Whole-Slide Images Analysis via Modeling of the Tumor Microenvironment and Biological Pathways
Junzhuo Liu, Xuemei Du, Daniel Reisenbuchler +5
Automatic integration of whole slide images (WSIs) and gene expression profiles has demonstrated substantial potential in precision clinical diagnosis and cancer progression studie…
Automatic Extraction of Rules for Generating Synthetic Patient Data From Real-World Population Data Using Glioblastoma as an Example
Arno Appenzeller, Nick Terzer, André Homeyer +10
The generation of synthetic data is a promising technology to make medical data available for secondary use in a privacy-compliant manner. A popular method for creating realistic p…
Resource Efficient Multi-stain Kidney Glomeruli Segmentation via Self-supervision
Zeeshan Nisar, Friedrich Feuerhake, Thomas Lampert
Semantic segmentation under domain shift remains a fundamental challenge in computer vision, particularly when labelled training data is scarce. This challenge is particularly exem…
Spatial Transcriptomics Expression Prediction from Histopathology Based on Cross-Modal Mask Reconstruction and Contrastive Learning
Junzhuo Liu, Markus Eckstein, Zhixiang Wang +2
Spatial transcriptomics is a technology that captures gene expression levels at different spatial locations, widely used in tumor microenvironment analysis and molecular profiling…