most citedCorrelation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network

1 citations · 1 across the 1 of their papers we have counts for

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2 papers

cs.CV2019★ 1 cited

Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network

Ziyue Xu, Xiaosong Wang, Hoo-Chang Shin +5

Radiogenomic map linking image features and gene expression profiles is useful for noninvasively identifying molecular properties of a particular type of disease. Conventionally, s…

cs.CV2016

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

Fausto Milletari, Nassir Navab, Seyed-Ahmad Ahmadi

Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields. Despite their popularity, most a…