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Class-Aware Adversarial Lung Nodule Synthesis in CT Images
[article]
2018
arXiv
pre-print
Though large-scale datasets are essential for training deep learning systems, it is expensive to scale up the collection of medical imaging datasets. Synthesizing the objects of interests, such as lung nodules, in medical images based on the distribution of annotated datasets can be helpful for improving the supervised learning tasks, especially when the datasets are limited by size and class balance. In this paper, we propose the class-aware adversarial synthesis framework to synthesize lung
arXiv:1812.11204v1
fatcat:ti3ykgz6irdhvptzwzuieasyw4