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A two-stage 3D Unet framework for multi-class segmentation on full resolution image

12 Apr 2018 • Chengjia Wang • Tom MacGillivray • Gillian Macnaught • Guang Yang • David Newby

Deep convolutional neural networks (CNNs) have been intensively used for multi-class segmentation of data from different modalities and achieved state-of-the-art performances. However, a common problem when dealing with large, high resolution 3D data is that the volumes input into the deep CNNs has to be either cropped or downsampled due to limited memory capacity of computing devices... (read more)

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