Raw data are the values of all measured detector signals during a scan. After calibration for fluctuations in tube output and beam hardening, the attenuation properties of each x-ray signal are accounted and correlated with the ray position. From these data the CT images are reconstructed including the use of mathematical procedures like convolution filtering and back projection.
Raw data can also be used for later reconstruction of additional planes and images by using a different convolution filter, zoom reconstruction, or an alternative CT number scale.

See also Magnification, Archiving, Number of Measurements and Convolution.

This term usually refers to the storage of patient data and images. Images are best archived in digital form (e.g., on optical disks, DVDs, PACS systems) and not only on films (hard copies, prints). Data compression via a reduction in matrix size, pixel depth or CT numbers, will result in a loss of spatial and contrast resolution. Digital images should be converted into a universal format such as DICOM. Raw data saving is necessary when additional image reconstructions are required.

See also Picture Archiving and Communication System, and Digital Imaging and Communications in Medicine.

Convolution is an important mathematical technique in digital signal processing. Raw data undergo spatial filtration prior to back projection by combining two signals to form a third signal. Convolution is related to the input signal, the output signal, and the impulse response. This operation is mostly used together with Fourier transformations for CT signal and image processing.

A convolution filter is a mathematical filter function (also called kernel). During image reconstruction of computed tomography scans, various types of convolution filters e.g., to smooth or to enhance edges, can be selected according to the tissue characteristics.

See also Raw Data.

(FT) The Fourier transformation is a mathematical procedure to separate out the frequency components of a signal from its amplitudes as a function of time, or the inverse Fourier transformation (IFT) calculates the time domain from the frequency domain. Fourier transformation analysis allows spatial information to be reconstructed from the raw data.