An aggregation of aggregation methods in computational pathology

Author:

Bilal MohsinORCID,Jewsbury RobertORCID,Wang Ruoyu,AlGhamdi Hammam M.ORCID,Asif Amina,Eastwood Mark,Rajpoot NasirORCID

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference90 articles.

1. Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the digital pathology association;Abels;J. Pathol.,2019

2. A survey on graph-based deep learning for computational histopathology;Ahmedt-Aristizabal;Comput. Med. Imaging Graph.,2022

3. A novel cell map representation for weakly supervised prediction of ER & PR status from H&E WSIs;AlGhamdi;Proc. MICCAI Workshop Comput. Pathol.,2021

4. Learning whole-slide segmentation from inexact and incomplete labels using tissue graphs;Anklin,2021

5. Towards Launching AI Algorithms for Cellular Pathology into Clinical & Pharmaceutical Orbits;Asif,2021

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