1 code implementation • ECCV 2020 • Mahdi S. Hosseini, Lyndon Chan, Weimin Huang, Yichen Wang, Danial Hasan, Corwyn Rowsell, Savvas Damaskinos, Konstantinos N. Plataniotis
Deep learning tools in computational pathology, unlike natural vision tasks, face with limited histological tissue labels for classification.
no code implementations • 11 Apr 2023 • Mahdi S. Hosseini, Babak Ehteshami Bejnordi, Vincent Quoc-Huy Trinh, Danial Hasan, Xingwen Li, Taehyo Kim, Haochen Zhang, Theodore Wu, Kajanan Chinniah, Sina Maghsoudlou, Ryan Zhang, Stephen Yang, Jiadai Zhu, Lyndon Chan, Samir Khaki, Andrei Buin, Fatemeh Chaji, Ala Salehi, Bich Ngoc Nguyen, Dimitris Samaras, Konstantinos N. Plataniotis
Computational Pathology CPath is an interdisciplinary science that augments developments of computational approaches to analyze and model medical histopathology images.
1 code implementation • 24 Dec 2019 • Lyndon Chan, Mahdi S. Hosseini, Konstantinos N. Plataniotis
Our experiments indicate that histopathology and satellite images present a different set of problems for weakly-supervised semantic segmentation than natural scene images, such as ambiguous boundaries and class co-occurrence.
1 code implementation • ICCV 2019 • Lyndon Chan, Mahdi S. Hosseini, Corwyn Rowsell, Konstantinos N. Plataniotis, Savvas Damaskinos
In digital pathology, tissue slides are scanned into Whole Slide Images (WSI) and pathologists first screen for diagnostically-relevant Regions of Interest (ROIs) before reviewing them.
1 code implementation • 14 Nov 2018 • Mahdi S. Hosseini, Yueyang Zhang, Lyndon Chan, Konstantinos N. Plataniotis, Jasper A. Z. Brawley-Hayes, Savvas Damaskinos
We also extend our method to generate a local slide-level focus quality heatmap, which can be used for automated slide quality control, and demonstrate the utility of our method for clinical scan quality control by comparison with subjective slide quality scores.