CountPath: Automating Fragment Counting in Digital Pathology

no code implementations • 13 Mar 2025 • Ana Beatriz Vieira, Maria Valente, Diana Montezuma, Tomé Albuquerque, Liliana Ribeiro, Domingos Oliveira, João Monteiro, Sofia Gonçalves, Isabel M. Pinto, Jaime S. Cardoso, Arlindo L. Oliveira

Quality control of medical images is a critical component of digital pathology, ensuring that diagnostic images meet required standards.

Diagnostic

An interpretable machine learning system for colorectal cancer diagnosis from pathology slides

no code implementations • 6 Jan 2023 • Pedro C. Neto, Diana Montezuma, Sara P. Oliveira, Domingos Oliveira, João Fraga, Ana Monteiro, João Monteiro, Liliana Ribeiro, Sofia Gonçalves, Stefan Reinhard, Inti Zlobec, Isabel M. Pinto, Jaime S. Cardoso

On the internal dataset, the method shows an accuracy of 93. 44% and a sensitivity between positive (low-grade and high-grade dysplasia) and non-neoplastic samples of 0. 996.

Active Learning Interpretable Machine Learning +1

CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance

no code implementations • Scientific Reports 2021 • Sara P. Oliveira, Pedro C. Neto, João Fraga, Diana Montezuma, Ana Monteiro, João Monteiro, Liliana Ribeiro, Sofia Gonçalves, Isabel M. Pinto, Jaime S. Cardoso

Most oncological cases can be detected by imaging techniques, but diagnosis is based on pathological assessment of tissue samples.

Colorectal Polyps Characterization whole slide images