What is the name of the filter applied to raw data during reconstruction to reduce blurring artifacts?

The process of reducing blurring artifacts during the reconstruction of raw data in computed tomography involves the application of specific filters. The term referred to in this context is an algorithm. Algorithms used in CT reconstruction manipulate the raw data by applying mathematical techniques to refine the image quality, improve resolution, and reduce artifacts.

In CT imaging, reconstruction algorithms work by processing the raw data to ensure that the final images are as clear and accurate as possible. These algorithms analyze the data from different angles and apply transformations to enhance the structural information present in the images, effectively mitigating effects such as blurring that may occur due to inherent imperfections in the imaging process.

The other choices refer to concepts or filters that may exist within imaging but do not specify the precise application to the raw data reconstruction process in CT scanning. While deconvolution filters and sharpening filters are used in various forms of image processing to enhance resolution and clarity, they do not encompass the foundational computational approach of reconstruction algorithms, which is critical in the context of this question.