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METHOD AND SYSTEM UTILIZING PARAMETER-LESS FILTER FOR SUBSTANTIALLY REDUCING STREAK AND OR NOISE IN COMPUTER TOMOGRAPHY (CT) IMAGES
METHOD AND SYSTEM UTILIZING PARAMETER-LESS FILTER FOR SUBSTANTIALLY REDUCING STREAK AND OR NOISE IN COMPUTER TOMOGRAPHY (CT) IMAGES
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机译：利用无参数滤波器来大大减少计算机断层扫描（CT）图像中的条纹和/或噪声的方法和系统
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摘要
Photon starvation causes streaks and noise and seriously impairs the diagnostic value of the CT imaging. To reduce streaks and noise, a new scheme of adaptive Gaussian filtering relies on the diffusion-derived scale-space concept in one embodiment of the current invention. In scale-space view, filtering by Gaussians of different sizes is similar to decompose the data into a sequence of scales. As the scale measure, the variance of the filter linearly relates to the noise standard deviation of a predetermined noise model in the new filtering method. The new filter has only one optional parameter that remains stable once tuned. Although single-pass processing using the new filter generally achieves desired results, iterations are optionally performed.
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