Publications de Christian Robert Abbet

Self-Supervised Learning for Patient Stratification and Survival Analysis in Computational Pathology: An Application to Colorectal Cancer

Over the years, clinical institutes accumulated large amounts of digital slides from resected tissue specimens. These digital images, called whole slide images (WSIs), are high-resolution tissue snapshots that depict the complex interaction of cells at the ...

EPFL2023

Pathologist Computer-Aided Diagnostic Scoring of Tumor Cell Fraction: A Swiss National Study

Christian Robert Abbet

Tumor cell fraction (TCF) estimation is a common clinical task with well-established large interobserver variability. It thus provides an ideal test bed to evaluate potential impacts of employing a tumor cell fraction computer-aided diagnostic (TCFCAD) too ...

Elsevier Science Inc2023

Self-supervised learning-based cervical cytology for the triage of HPV-positive women in resource-limited settings and low-data regime

Jean-Philippe Thiran, Christian Robert Abbet, Thomas Grégoire Stegmüller, Seyedbehzad Bozorgtabar

Screening Papanicolaou test samples has proven to be highly effective in reducing cervical cancer-related mortality. However, the lack of trained cytopathologists hinders its widespread implementation in low-resource settings. Deep learning-assisted telecy ...

Pergamon-Elsevier Science Ltd2023

Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection

Jean-Philippe Thiran, Christian Robert Abbet, Seyedbehzad Bozorgtabar

Supervised learning is constrained by the availability of labeled data, which are especially expensive to acquire in the field of digital pathology. Making use of open-source data for pre-training or using domain adaptation can be a way to overcome this is ...

ELSEVIER2022

Beekeeping - artificial neural networks to fight varroa

Jean-Philippe Thiran, Mohammad Saeed Rad, Christian Robert Abbet, Maxime Camille Bohnenblust, Roser Vinals Terres, Alain Bugnon

AGRARFORSCHUNG2021

Divide-and-Rule: Self- Supervised Learning for Survival Analysis in Colorectal Cancer

Jean-Philippe Thiran, Christian Robert Abbet, Seyedbehzad Bozorgtabar, Inti Zlobec

2020