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Guillaume Thibault

Researcher at Oregon Health & Science University

Publications -  108
Citations -  4358

Guillaume Thibault is an academic researcher from Oregon Health & Science University. The author has contributed to research in topics: Unfolded protein response & Endoplasmic reticulum. The author has an hindex of 26, co-authored 99 publications receiving 3193 citations. Previous affiliations of Guillaume Thibault include Agency for Science, Technology and Research & University of Toronto.

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Quantitative Multiplex Immunohistochemistry Reveals Myeloid-Inflamed Tumor-Immune Complexity Associated with Poor Prognosis

TL;DR: A multiplexed immunohistochemical platform with computational image processing workflows, including image cytometry, enabling simultaneous evaluation of 12 biomarkers in one formalin-fixed paraffin-embedded tissue section is described, revealing differential immune profiles based on lymphoid and myeloid cell densities, correlating with human papilloma virus status and prognosis.
Journal ArticleDOI

TeleOphta: Machine learning and image processing methods for teleophthalmology

TL;DR: In this paper, a complete prototype for the automatic detection of normal examinations on a teleophthalmology network for diabetic retinopathy screening is presented, which combines pathological pattern mining methods, with specific lesion detection methods, to extract information from the images.

Iconography : TeleOphta: Machine learning and image processing methods for teleophthalmology

TL;DR: A complete prototype for the automatic detection of normal examinations on a teleophthalmology network for diabetic retinopathy screening is presented, which combines pathological pattern mining methods with specific lesion detection methods to extract information from the images.
Journal ArticleDOI

The Human Tumor Atlas Network: Charting Tumor Transitions Across Space and Time at Single-Cell Resolution

Orit Rozenblatt-Rosen, +373 more
- 16 Apr 2020 - 
TL;DR: The Human Tumor Atlas Network (HTAN), part of the NCI Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types.
Proceedings Article

Texture indexes and gray level size zone matrix. Application to cell nuclei classification

TL;DR: A study on the characterization and the classification of textures using a set of values obtained by the computation of indexes, which are proposed to classify cells nuclei in order to diagnose patients affected by the Progeria disease.