Christopher Ross
4 Papers
1 Citations
Christopher Ross is an academic researcher. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 2, co-authored 4 publications.
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Papers
A digital pathology workflow for the segmentation and classification of gastric glands: Study of gastric atrophy and intestinal metaplasia cases
Panagiotis Barmpoutis,William Waddingham,Jing Yun Yuan,Christopher Ross,Hamzeh Kayhanian,Tania Stathaki,Daniel C. Alexander,Marnix Jansen +7 more
TL;DR: In this paper , an end-to-end workflow for gastric gland segmentation and classification for the analysis of gastric tissues is proposed. But, it is difficult to confirm endoscopically and, following the Sydney protocol, their diagnosis depends on the diagnosis of glandular morphology and on the identification of at least one well-defined goblet cell in a set of hematoxylin and eosin (H&E)-stained biopsy samples.
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Mutation Rate Evolution Drives Immune Escape In Mismatch Repair-Deficient Cancer
Hamzeh Kayhanian,Panagiotis Barmpoutis,Eszter Lakatos,William Cross,Giulio Caravagna,Luis Zapata,Kevin Litchfield,Christopher D. Steele,William Waddingham,Dominic Patel,Salvatore Milite,Chen Jin,Ann-Marie Baker,Christopher Ross,Daniel Alexander,Khurum Khan,Daniel Hochhauser,Marco Novelli,Benjamin Werner,Naomi Guppy,Josep Linares,Marjolijn J. L. Ligtenberg,Iris D. Nagtegaal,Andrea Sottoriva,Trevor A. Graham,Nischalan Pillay,Manuel Rodriguez-Justo,Kai-Keen Shiu,Marnix Jansen +28 more
TL;DR: Mapping the clonal topography of mismatch repair-deficient MMRd colorectal cancer shows that genomic MMRd mutability co-evolves with neoantigen selection to drive intratumour diversification and immune escape, and reveals layers of mutational complexity and microsatellite biology in MMRd cancer evolution previously hidden in bulk analyses.
3
Gland segmentation in gastric histology images: detection of intestinal metaplasia
Panagiotis Barmpoutis,William Waddingham,Christopher Ross,Hamzeh Kayhanian,Daniel C. Alexander,Marnix Jansen +5 more
- 29 Aug 2022
TL;DR: A framework for segmentation of gastric glands and detection of IM is proposed and the proposed methodology shows great potential for the IM detection achieving an accuracy score equal to 96.6%.
Multi-scale Deformable Transformer for the Classification of Gastric Glands: The IMGL Dataset
Panagiotis Barmpoutis,Jing Yun Yuan,William Waddingham,Christopher Ross,Hamzeh Kayhanian,Tania Stathaki,Daniel C. Alexander,Marnix Jansen +7 more
TL;DR: In this article , a deformable transformer-based network was proposed for the classification of gastric glands into normal and IM gastric cells, which achieved an F1 score equal to 0.94.