Search Results for author: Roberto Salgado

Found 3 papers, 2 papers with code

ECTIL: Label-efficient Computational Tumour Infiltrating Lymphocyte (TIL) assessment in breast cancer: Multicentre validation in 2,340 patients with breast cancer

2 code implementations • 24 Jan 2025 • Yoni Schirris, Rosie Voorthuis, Mark Opdam, Marte Liefaard, Gabe S Sonke, Gwen Dackus, Vincent de Jong, Yuwei Wang, Annelot Van Rossum, Tessa G Steenbruggen, Lars C Steggink, Liesbeth G. E. de Vries, Marc van de Vijver, Roberto Salgado, Efstratios Gavves, Paul J van Diest, Sabine C Linn, Jonas Teuwen, Renee Menezes, Marleen Kok, Hugo Horlings

We propose and validate a fundamentally simpler deep learning based CTA that can be trained in only ten minutes on hundredfold fewer pathologist annotations.

Diagnostic whole slide images

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Code

Automated Scoring of Nuclear Pleomorphism Spectrum with Pathologist-level Performance in Breast Cancer

no code implementations • 9 Dec 2020 • Caner Mercan, Maschenka Balkenhol, Roberto Salgado, Mark Sherman, Philippe Vielh, Willem Vreuls, Antonio Polonia, Hugo M. Horlings, Wilko Weichert, Jodi M. Carter, Peter Bult, Matthias Christgen, Carsten Denkert, Koen van de Vijver, Jeroen van der Laak, Francesco Ciompi

Nuclear pleomorphism, defined herein as the extent of abnormalities in the overall appearance of tumor nuclei, is one of the components of the three-tiered breast cancer grading.

whole slide images

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Self-Supervised Nuclei Segmentation in Histopathological Images Using Attention

1 code implementation • 16 Jul 2020 • Mihir Sahasrabudhe, Stergios Christodoulidis, Roberto Salgado, Stefan Michiels, Sherene Loi, Fabrice André, Nikos Paragios, Maria Vakalopoulou

We show that the identification of the magnification level for tiles can generate a preliminary self-supervision signal to locate nuclei.

Segmentation

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