A conditional GAN fuses gene expression profiles with background images at multiple scales to generate synthetic nodule images and learn radiogenomic correlations end-to-end on NSCLC data.
IEEE Transactions on Medical Imaging 35(5), 1285–1298 (May 2016)
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Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network
A conditional GAN fuses gene expression profiles with background images at multiple scales to generate synthetic nodule images and learn radiogenomic correlations end-to-end on NSCLC data.