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Random transformations are commonly used for augmentation of the trainingdata with the goal of reducing the uniformity of the training samples. Thesetransformations normally aim at variations that can be expected in images fromthe same modality. Here, we propose a simple method for transforming the grayvalues of an image with the goal of reducing cross modality differences. Thisapproach enables segmentation of the lumbar vertebral bodies in CT images usinga network trained exclusively with MR images. The source code is made availableat https://github.com/nlessmann/rsgt

Random smooth gray value transformations for cross modality learning with gray value invariant networks