Abstract: We bring together into a common framework three key ideas — multi-scale medical image analysis, the attention mechanism, and hyperbolic embeddings. The formulation and evaluation of hyperbolic-attention models for multi-scale medical image analysis have not been previously explored. In this paper, we evaluate a hyperbolic-attention model on two classification tasks using histopathology image datasets. The experiments show improvement compared to other commonly used models. Our method directly captures the multi-scale structure of histopathology images, and we speculate that the hyperbolic attention mechanism naturally singles out one or more structures at one or more scales that are most discriminatory.
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