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Overcoming the limitations of patch-based learning to detect cancer in whole slide images
We apply a binary cancer detection network on post neoadjuvant therapy breast cancer WSIs to find the tumor bed outlining the extent of cancer, a task which requires sensitivity and precision across the whole slide.
Transitioning between Convolutional and Fully Connected Layers in Neural Networks
Digital pathology has advanced substantially over the last decade however tumor localization continues to be a challenging problem due to highly complex patterns and textures in the underlying tissue bed.
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