Rittscher group | Quantitative biological imaging
Prof. Jens Rittscher
The overall goal of my research is to enable quantitative biological imaging through the development of new algorithms and computational platforms. Our work at the Ludwig aims to improve mechanistic understanding of cancer and patient care.
Here we are building on our expertise in biomedical image analysis, computer vision and machine learning to find new and effective ways to extract information from complex from large biomedical image data sets. In particular, computational tools we develop address:
- Understanding molecular mechanisms – We study morphological changes and motion patters at the single cell and population levels to investigate mechanisms of migration and invasion.
- Clinical management and diagnosis – By extracting quantitative information from digitized histology images and high-resolution endoscopy data, we aim to improve the quality and consistency of clinical decision-making.
- Systematic integration of multi-modal data – In order to understand complex questions involving the evaluation of new treatments or the identification of disease subtypes, we require the integration of imaging data with other molecular and genetic information.
Our team
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Jens Rittscher
Professor of Engineering Science
Latest Rittscher group news
Automated assessment of pathology image quality
6 April 2022
Recent publications
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Tumor NOS2 and COX2 Spatial Juxtaposition with CD8+ T Cells Promote Metastatic and Cancer Stem Cell Niches that Lead to Poor Outcome in ER- Breast Cancer.
Journal article
Ridnour LA. et al, (2024), Cancer Res Commun
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Quantitative analysis of bone marrow fibrosis highlights heterogeneity in myelofibrosis and augments histological assessment: An Insight from a phase II clinical study of zinpentraxin alfa
Journal article
Ryou H. et al, (2024), HemaSphere, 8
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SSL-CPCD: Self-supervised learning with composite pretext-class discrimination for improved generalisability in endoscopic image analysis.
Journal article
Xu Z. et al, (2024), IEEE transactions on medical imaging, PP