Encoder regularization of a segmentation model

    公开(公告)号:US10740901B2

    公开(公告)日:2020-08-11

    申请号:US16223005

    申请日:2018-12-17

    Inventor: Andriy Myronenko

    Abstract: A segmentation model is trained with an image reconstruction model that shares an encoding. During application of the segmentation model, the segmentation model may use the encoding and network layers trained for the segmentation without the image reconstruction model. The image reconstruction model may include a probabilistic representation of the image that represents the image based on a probability distribution. When training the model, the encoding layers of the model use a loss function including an error term from the segmentation model and from the autoencoder model. The image reconstruction model thus regularizes the encoding layers and improves modeling results and prevents overfitting, particularly for small training sizes.

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