Pathology-Aware Generative Adversarial Networks for Medical Image Augmentation.
Abstract
Convolutional Neural Networks (CNNs) can play a key role in Medical Image Analysis under large-scale annotated datasets. However, preparing such massive dataset is demanding. In this context, Generative Adversarial Networks (GANs) can generate realistic but novel samples, and thus effectively cover the real image distribution. In terms of interpolation, the GAN-based medical image augmentation is reliable because medical modalities can display...
Paper Details
Title
Pathology-Aware Generative Adversarial Networks for Medical Image Augmentation.
Published Date
Jun 3, 2021
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