Schaller Stefan, Wildberger J E, Raupach Rainer, Niethammer Matthias, Klingenbeck-Regn Klaus, Flohr Thomas
Siemens AG, Medical Solutions, Computed Tomography Division, Siemensstr. 1, 91301 Forchheim, Germany.
IEEE Trans Med Imaging. 2003 Jul;22(7):846-53. doi: 10.1109/TMI.2003.815073.
In computed tomography (CT), selection of a convolution kernel determines the tradeoff between image sharpness and pixel noise. For certain clinical applications it is desirable to have two or more sets of images with different settings. So far, this typically requires reconstruction of several sets of images. We present an alternative approach using default reconstruction of sharp images and online filtering in the spatial domain allowing modification of the sharpness-noise tradeoff in real time. A suitable smoothing filter function in the frequency domain is the ratio of smooth and original (sharp) kernel. Efficient implementation can be achieved by a Fourier transform of this ratio to the spatial domain. Separating the two-dimensional spatial filtering into two subsequent one-dimensional filtering stages in the x and y directions using a Gaussian approximation for the convolution kernel further reduces computational complexity. Due to efficient implementation, interactive modification of the filter settings becomes possible, which can completely replace the variety of different reconstruction kernels.
在计算机断层扫描（CT）中，卷积核的选择决定了图像清晰度与像素噪声之间的权衡。对于某些临床应用而言，需要有两组或更多组具有不同设置的图像。到目前为止，这通常需要重建多组图像。我们提出了一种替代方法，即使用清晰图像的默认重建以及空间域中的在线滤波，从而能够实时修改清晰度-噪声权衡。频域中合适的平滑滤波函数是平滑核与原始（清晰）核的比值。通过将该比值进行傅里叶变换到空间域，可以实现高效的实现。使用卷积核的高斯近似将二维空间滤波分离为x和y方向上的两个后续一维滤波阶段，进一步降低了计算复杂度。由于实现高效，因此可以对滤波设置进行交互式修改，这完全可以替代各种不同的重建核。
