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Stéphane Sockeel

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV1
  • eess.IV1
  • q-bio.TO1
ORCID 0000-0002-6762-9028

identity via Semantic Scholar / OpenAlex

most citedMulticenter automatic detection of invasive carcinoma on breast whole slide images

3 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

q-bio.TO2023

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…

cs.CV2023★ 1 cited

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…

eess.IV2023★ 3 cited

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.