3 citations · 8 across the 6 of their papers we have counts for
4 papers · 1 filter
Classification in Histopathology: A unique deep embeddings extractor for multiple classification tasks
Adrien Nivaggioli, Nicolas Pozin, Rémy Peyret +6
In biomedical imaging, deep learning-based methods are state-of-the-art for every modality (virtual slides, MRI, etc.) In histopathology, these methods can be used to detect certai…
Convolutional Neural Network-Based Automatic Classification of Colorectal and Prostate Tumor Biopsies Using Multispectral Imagery: System Development Study
Remy Peyret, Duaa alSaeed, Fouad Khelifi +3
Colorectal and prostate cancers are the most common types of cancer in men worldwide. To diagnose colorectal and prostate cancer, a pathologist performs a histological analysis on…
Multicenter automatic detection of invasive carcinoma on breast whole slide images
Rémy Peyret, Nicolas Pozin, Stéphane Sockeel +10
Breast cancer is one of the most prevalent cancers worldwide and pathologists are closely involved in establishing a diagnosis. Tools to assist in making a diagnosis are required t…
Standardized CycleGAN training for unsupervised stain adaptation in invasive carcinoma classification for breast histopathology
Nicolas Nerrienet, Rémy Peyret, Marie Sockeel +1
Generalization is one of the main challenges of computational pathology. Slide preparation heterogeneity and the diversity of scanners lead to poor model performance when used on d…