Segmentation of Liver Lesions with Reduced Complexity Deep Models

We propose a computationally efficient architecture that learns to segment lesions from CT images of the liver. The proposed architecture uses bilinear interpolation with sub-pixel convolution at the last layer to upscale the course feature in bottle neck architecture... (read more)

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