Guillaume Thibault

CROCHET: a versatile pipeline for automated analysis and visual atlas creation from single-cell spatialomic data

CROCHET is a pipeline for automated analysis of single-cell spatialomic data and creation of visual atlases, supporting diverse data modalities and downstream analyses.

A spatially resolved single cell proteomic atlas of Small Bowel Adenocarcinoma

This study creates a spatial proteomic atlas of SBA tumor-immune microenvironment, revealing cell interactions and immune checkpoint patterns linked to patient survival and therapy.

AxonFinder: Automated segmentation of tumor innervating neuronal fibers

AxonFinder segments axons in prostate tumor microenvironments using deep learning, showing correlation between axon density and cancer risk.

SEG: Segmentation Evaluation in absence of Ground truth labels

The paper introduces a method to evaluate segmentation performance in multiplex tissue imaging without ground truth labels by comparing segmentations from an ensemble of models.

Toward reproducible, scalable, and robust data analysis across multiplex tissue imaging platforms

The paper develops open-source tools for analyzing multiplex tissue imaging data and demonstrates their application on a human breast cancer dataset.

VISTA: Virtual ImmunoSTAining for pancreatic disease quantification in murine cohorts

The paper introduces a deep learning tool for automated histologic feature quantification in murine pancreatic disease models, showing high correlation with immunostaining results and accurate differentiation of disease states.

SHIFT: speedy histological-to-immunofluorescent translation of whole slide images enabled by deep learning

This paper introduces a deep learning method called SHIFT that translates histological images into virtual immunofluorescence images, improving efficiency and reducing costs in cancer diagnostics.

RESTORE: Robust intEnSiTy nORmalization mEthod for Multiplexed Imaging

RESTORE normalizes intensity variations in multiplexed imaging data by using negative control cells to remove background noise and improve sample integration.