3 citations · 4 across the 3 of their papers we have counts for
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cs.CV2024★ 3 cited
GRASP: GRAph-Structured Pyramidal Whole Slide Image Representation
Ali Khajegili Mirabadi, Graham Archibald, Amirali Darbandsari +9
Cancer subtyping is one of the most challenging tasks in digital pathology, where Multiple Instance Learning (MIL) by processing gigapixel whole slide images (WSIs) has been in the…
cs.CV2022★ 1 cited
CCRL: Contrastive Cell Representation Learning
Ramin Nakhli, Amirali Darbandsari, Hossein Farahani +1
Cell identification within the H&E slides is an essential prerequisite that can pave the way towards further pathology analyses including tissue classification, cancer grading, and…