论文标题
可视化医学图像融合和翻译，以准确诊断高级神经胶质瘤
Visualisation of Medical Image Fusion and Translation for Accurate Diagnosis of High Grade Gliomas
论文作者
论文摘要
医学图像融合将两种或多种模式结合到单个视图中，而医学图像翻译综合了新图像并有助于数据增强。总之，这些方法有助于更快地诊断出高级恶性神经胶质瘤。但是，它们可能是不可信的，因此，神经外科医生需要一种可靠的可视化工具来验证融合融合的可靠性和翻译结果，然后才能做出术前手术决策。在本文中，我们提出了一种新颖的方法，通过使用两个图像的关节概率分布估算信息从源到目标图像的信息传输，以在源目标图像对之间计算置信热图。我们使用我们的可视化程序评估了几种融合和翻译方法，并展示了其在使神经外科医生做出更精细的临床决策方面的鲁棒性。
The medical image fusion combines two or more modalities into a single view while medical image translation synthesizes new images and assists in data augmentation. Together, these methods help in faster diagnosis of high grade malignant gliomas. However, they might be untrustworthy due to which neurosurgeons demand a robust visualisation tool to verify the reliability of the fusion and translation results before they make pre-operative surgical decisions. In this paper, we propose a novel approach to compute a confidence heat map between the source-target image pair by estimating the information transfer from the source to the target image using the joint probability distribution of the two images. We evaluate several fusion and translation methods using our visualisation procedure and showcase its robustness in enabling neurosurgeons to make finer clinical decisions.
