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Fig. 1 | BMC Medical Imaging

Fig. 1

From: “A net for everyone”: fully personalized and unsupervised neural networks trained with longitudinal data from a single patient

Fig. 1

Architecture of the generator network. A U-Net structure is used. At each level there are two blocks of 3 × 3 convolution, batch normalization (BN) and ReLU. 2 × 2 Max pool functions are used for downsizing. 4 × 4 transposed convolutions with stride = 2 are used for upsizing. The size of the image at each level is shown on the left. The number of features in each block is shown on the top of the block

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BMC Medical Imaging

ISSN: 1471-2342

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