A novel method developed by graduate students from Kimia Lab, Waterloo Engineering, Mohammed Adnan (1st-year MASc.), and Shivam Kalra (2nd year Ph.D.) has the potential to have a major impact in histopathological image analysis and cancer diagnostics. Their technique uses artificial intelligence (AI) to render digital representations of extremely high-resolution biopsy images. These digital representations can be used for real-time image search, providing critical information to pathologists for well-informed and evidence-based diagnosis. Two of their works have been recently published in top machine learning conferences:
1) Representation
Learning
of
Histopathology
Images
using
Graph
Neural
Networks,
CVPR
2020
(CVMI
Workshop)
2) Learning
Permutation
Invariant
Representations
Using
Memory
Networks,
ECCV
2020