Monday, July 6, 2020

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

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