This study identifies an estrogen receptor signaling program in HR+ breast cancer that suppresses immune responses by reducing T cell infiltration and HLA expression, suggesting therapeutic targets to enhance immunogenicity.

bioRxiv · Nov 23, 2024 · PreprintCancer Biology

psudo: Exploring Multi-Channel Biomedical Image Data with Spatially and Perceptually Optimized Pseudocoloring

Simon Warchol, Jakob Troidl, Jeremy L. Muhlich, Robert Krueger, John Hoffer, Tica Lin, Johanna Beyer, Elena Leah Glassman, Peter Karl Sorger, Hanspeter Pfister

psudo is an interactive system that optimizes pseudocolor palettes for multichannel biomedical images to enhance perceptual distinction and reduce color confusion in overlapping channels.

Computer Graphics Forum · Jun 1, 2024Peer-reviewedCell Biology

Addressing persistent challenges in digital image analysis of cancerous tissues

Sandhya Prabhakaran, Clarence Yapp, Gregory J. Baker, Johanna Beyer, Young Hwan Chang, Allison Creason, Robert Krueger, Jeremy L. Muhlich, Nathan Heath Patterson, Kevin Sidak, Damir Sudar, Adam J. Taylor, Luke Ternes, Jakob Troidl, Yubin Xie, , the Cell Imaging Hackathon 2022 Participants (Alphabetical authorship, apart from primary contributors)

The paper discusses challenges in digital image analysis of cancerous tissues and outlines solutions developed during a 2022 hackathon.

bioRxiv · Jul 21, 2023 · PreprintBioinformatics

Facetto: Combining Unsupervised and Supervised Learning for Hierarchical Phenotype Analysis in Multi-Channel Image Data

Robert Krueger, Johanna Beyer, Won-Dong Jang, Nam Wook Kim, Artem Sokolov, Peter Karl Sorger, Hanspeter Pfister

Facetto combines unsupervised and supervised learning to analyze multi-channel microscopy images, enabling discovery of cell types and phenotypes in cancer tissues.

IEEE Transactions on Visualization and Computer Graphics · Sep 11, 2019Peer-reviewedSystems Biology