Ea-GANs: Edge-aware Generative Adversarial Networks for Cross-modality MR Image Synthesis
期刊：IEEE Trans Med Imaging Impact Factor: 6.1 時間：2019 研究背景 在臨牀中，對MRI多模態圖（e.g.,T1-weighted, T2-weighted）的綜合分析，有利於醫生對病情的瞭解。 由於多模態圖的缺失，或者不同機構影像設備不一致，使得MRI多模態圖的合成成爲熱點。 以往的合成圖像，更多的是追求像素值與真實數據相似，忽略其中的結構信息。 以
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