Multi-V-Stain: Multiplexed Virtual Staining of Histopathology Whole-Slide Images
Abstract
Pathological assessment on Hematoxylin & Eosin (H&E) stained tissue samples is a clinically-established routine for cancer diagnosis. While providing rich morphological information, it lacks insights on protein expression patterns, essential for cancer prognosis and treatment decisions. Imaging Mass Cytometry (IMC) is adept at highly multiplexed protein profiling. However, it has challenges such as high operational cost and a restrictive focus on small Regions-of-Interest. To this end, we propose Multi-V-Stain, a novel image-to-image translation method for multiplexed IMC virtual staining. Our method can effectively leverage the rich morphological features from H&E images to predict multiplexed protein expressions on a Whole-Slide Image level. In our assessments using an in-house melanoma dataset, Multi-V-Stain consistently achieves higher image quality and generates stains that are more biologically relevant when compared to existing techniques. Show more
Publication status
publishedBook title
Deep Generative Models for Health Workshop NeurIPS 2023Publisher
OpenReviewEvent
Organisational unit
09568 - Rätsch, Gunnar / Rätsch, Gunnar
09735 - Bodenmiller, Bernd / Bodenmiller, Bernd
Notes
Poster presentation on December 15, 2023.More
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ETH Bibliography
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