体素
能见度
噪音(视频)
图像噪声
计算机视觉
滤波器(信号处理)
人工智能
统计噪声
平滑的
光圈(计算机存储器)
医学
对比度(视觉)
衰减
计算机科学
光学
图像(数学)
物理
声学
机器学习
出处
期刊:Radiographics
[Radiological Society of North America]
日期:1992-09-01
卷期号:12 (5): 1041-1046
被引量:78
标识
DOI:10.1148/radiographics.12.5.1529128
摘要
Two important characteristics of the computed tomographic (CT) image that affect the ability to visualize anatomic structures and pathologic features are blur and noise. Increased blurring reduces the visibility of small objects (image detail); increased visual noise reduces the visibility of low-contrast objects. Sources of blurring in CT include the size of the sampling aperture (which can be regulated by the focal spot size and the detector size), the size of the voxels, and the reconstruction filter selected. Noise is caused by the variation in attenuation coefficients between voxels. Use of small voxels and edge-enhancing filters helps reduce blurring and improve visibility of fine details. However, small voxels absorb fewer photons and therefore result in increased noise. Noise can be reduced by using large voxels, increasing radiation dose, or using a smoothing filter, but this filter increases blurring. An optimized protocol for a specific clinical study must take these physical principles into account and be adjusted to give proper balance among detail, low noise, and patient exposure.
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