It is well-known that the human visual system is adapted to the statistical structure of natural scenes. Yet there are important classes of images – for example, medical images – that are not natural scenes, and therefore, that are expected to have statistical properties that deviate from the class of images that shaped the evolution and development of human vision. Here, focusing on structural brain MRI images, we quantify and characterize these deviations in terms of a set of local image statistics to which human visual sensitivity has been well-characterized, and that has previously been used for natural image analysis. We analyzed MRI images in multiple databases including T1-weighted and FLAIR sequence types, and simulated MRI images based on a published image simulation procedure for T1 images, which we also modified to generate FLAIR images. We first computed the power spectra of MRI images; spectral slopes were in the range −2.6 to −3.1 for T1 sequences, and −2.2 to −2.7 for FLAIR sequences. Analysis of local image statistics was then carried out on whitened images. For all of the databases as well as for the simulated images, we found that the three-point correlations contributed substantially to the differences between the “texture” of randomly selected ROIs. The informative nature of three-point correlations for brain MRI was greater than for natural images, and also disproportionate to human visual sensitivity. As this finding was consistent across databases, it is likely to result from brain geometry at the scale of brain MRI resolution, rather than characteristics of specific imaging and reconstruction methods.

中文翻译：

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脑 MRI 感知相关图像统计与自然图像之间的系统差异

众所周知，人类视觉系统适应自然场景的统计结构。然而，有一些重要的图像类别（例如医学图像）不是自然场景，因此预计其统计特性与塑造人类视觉进化和发展的图像类别不同。在这里，我们重点关注结构性脑部 MRI 图像，根据一组局部图像统计数据来量化和表征这些偏差，人类视觉敏感性已被很好地表征，并且之前已用于自然图像分析。我们分析了多个数据库中的 MRI 图像，包括 T1 加权和 FLAIR 序列类型，并根据已发布的 T1 图像图像模拟程序模拟 MRI 图像，我们还对其进行了修改以生成 FLAIR 图像。我们首先计算了 MRI 图像的功率谱；T1 序列的光谱斜率范围为-2.6 至-3.1，FLAIR 序列的光谱斜率范围为-2.2 至-2.7。然后对白化图像进行局部图像统计分析。对于所有数据库以及模拟图像，我们发现三点相关性很大程度上导致了随机选择的 ROI 的“纹理”之间的差异。脑 MRI 的三点相关性的信息量大于自然图像，并且与人类视觉灵敏度不成比例。由于这一发现在各个数据库中是一致的，因此它很可能是由脑 MRI 分辨率范围内的脑几何结构产生的，而不是特定成像和重建方法的特征。