IEEE Trans Med Imaging. 2018 Aug;37(8):1788-1798. doi: 10.1109/TMI.2018.2806878. Epub 2018 Feb 15.
Microwave radar imaging is promising as a complementary medical imaging modality. However, the unique nature of the images means interpretation can be difficult. As a result, it is important to understand the sources of image differences, and how much variability is inherent in the imaging system itself. To address this issue, we compare the effectiveness of six different measures of image similarity for quantifying the similarity (or difference) between two microwave radar images. The structural similarity index has become the de facto standard for image comparison, but we propose that useful information can be acquired from a measure known as the Modified Hausdorff Distance. We apply each measure to image pairs from sequential scans of both phantoms and volunteers. We find that rather than using a single value to quantify the image similarity, by computing a number of values that are designed to capture different image aspects, we can better assess the ways in which the images differ.
微波雷达成像是一种很有前途的医学成像辅助手段。然而，由于图像的独特性质，其解释可能较为困难。因此，了解图像差异的来源以及成像系统本身固有的可变性程度非常重要。为了解决这个问题，我们比较了六种不同的图像相似性度量方法，以量化两幅微波雷达图像之间的相似性（或差异）。结构相似性指数已成为图像比较的事实上的标准，但我们提出，一种称为修正的 Hausdorff 距离的度量方法可以提供有用的信息。我们将每种方法应用于来自对模型和志愿者进行的连续扫描的图像对。我们发现，通过计算旨在捕捉不同图像方面的多个值，而不是使用单个值来量化图像相似性，我们可以更好地评估图像之间的差异方式。
