Kernel (image reconstruction for CT)

Last revised by Andrew Murphy on 23 Mar 2023

The kernel, also known as a convolution algorithm, refers to the process used to modify the frequency contents of projection data prior to back projection during image reconstruction in a CT scanner 1. This process corrects the image by reducing blurring 1. The kernel affects the appearance of image structures by sharpening the image. Different kernels have been developed for specific anatomical applications including soft tissue (standard kernel) and bone (bone kernel) 2. Bone kernels produce a sharper image with higher spatial resolution 1.

When this kind of algorithm is used to improve spatial resolution, the process is called deconvolution. The process of deconvolution coupled with back projection results in filtered back projection 2.

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