2 citations · 2 across the 3 of their papers we have counts for
5 papers
A New Era in Computational Pathology: A Survey on Foundation and Vision-Language Models
Dibaloke Chanda, Milan Aryal, Nasim Yahya Soltani +1
Recent advances in deep learning have completely transformed the domain of computational pathology (CPath). More specifically, it has altered the diagnostic workflow of pathologist…
Adversary-Robust Graph-Based Learning of WSIs
Saba Heidari Gheshlaghi, Milan Aryal, Nasim Yahyasoltani +1
Enhancing the robustness of deep learning models against adversarial attacks is crucial, especially in critical domains like healthcare where significant financial interests height…
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…
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…
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…