Automatic Data Augmentation via Deep Reinforcement Learning for Effective Kidney Tumor Segmentation

ICASSP, pp. 1419-1423, 2020.

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Abstract:

Conventional data augmentation realized by performing simple pre-processing operations (\eg, rotation, crop, \etc) has been validated for its advantage in enhancing the performance for medical image segmentation. However, the data generated by these conventional augmentation methods are random and sometimes harmful to the subsequent seg...More

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