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We propose a novel technique to incorporate attention within convolutionalneural networks using feature maps generated by a separate convolutionalautoencoder. Our attention architecture is well suited for incorporation withdeep convolutional networks. We evaluate our model on benchmark segmentationdatasets in skin cancer segmentation and lung lesion segmentation. Results showhighly competitive performance when compared with U-Net and it's residualvariant.

FocusNet: An attention-based Fully Convolutional Network for Medical Image Segmentation