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eess.IV2023
Artifact-Robust Graph-Based Learning in Digital Pathology
Saba Heidari Gheshlaghi, Milan Aryal, Nasim Yahyasoltani +1
Whole slide images~(WSIs) are digitized images of tissues placed in glass slides using advanced scanners. The digital processing of WSIs is challenging as they are gigapixel images…
eess.IV2023
Explainable and Position-Aware Learning in Digital Pathology
Milan Aryal, Nasim Yahyasoltani
Encoding whole slide images (WSI) as graphs is well motivated since it makes it possible for the gigapixel resolution WSI to be represented in its entirety for the purpose of graph…
eess.IV2023
Context-Aware Self-Supervised Learning of Whole Slide Images
Milan Aryal, Nasim Yahyasoltani
Presenting whole slide images (WSIs) as graph will enable a more efficient and accurate learning framework for cancer diagnosis. Due to the fact that a single WSI consists of billi…