1 citations · 2 across the 3 of their papers we have counts for
3 papers
Contrastive-Based Deep Embeddings for Label Noise-Resilient Histopathology Image Classification
Lucas Dedieu, Nicolas Nerrienet, Adrien Nivaggioli +5
Recent advancements in deep learning have proven highly effective in medical image classification, notably within histopathology. However, noisy labels represent a critical challen…
Evaluation of the mitotic score of invasive breast carcinomas on digital slide: development and contribution of a mitosis detection algorithm
Loris Guichard, Clara Simmat, Margot Dupeux +6
Introduction: Nottingham grading system is a major prognostic factor for invasive breast carcinoma (IBC). Its determination requires the evaluation of the mitotic score (MS) which…
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…