The reconstruction of objects from shadowgraphs with high contrasts

New iterative reconstruction techniques for cardiovascular computed tomography: How do they work, and what are the advantages and disadvantages?

“…Basically, a FBP is a technique whereby projections or views from the raw data are first filtered then back-projected to form a 2-dimensional array of voxels that are assigned a shade of gray proportionate to the average x-ray photon distribution of each voxel. [1][2][3][4][5][6] This reconstruction technique, however, has significant limitations, because it relies on several assumptions. These assumptions include the following: (1) the focal spot comprises a single point at the surface of the anode, (2) the x-ray beam is modeled as a pencil-shaped ray passing through the object being scanned, (3) there is a point-like interaction of the x-ray beam with the voxel in the patient or object being scanned, and (4) there is a point-like interaction of the x-ray beam with the detector.…”

“…[7][8][9] Clinical situations in which image quality tends to be less acceptable include: (1) CT scans in large patients (Fig. 1); (2) images with small voxels, such as the targeted field-of-view used for cardiac CT; (3) images through the bony pelvis; and (4) intentionally low-dose datasets. An alternative to the FBP is an iterative reconstruction (IR) that uses a maximum likelihood (ML) algorithm.…”

“…Filtered back projection (FBP) algorithms are currently the most widespread implementation of this technique. [1][2][3][4][5][6] The main advantages of the FBP include reconstruction speeds of %30-40 slices per second, overall robustness, and relatively acceptable image quality for most cases. The main disadvantage of the FBP is the overall limitations in image quality, mainly because of the back-projection process and the necessary filtering, which accentuates noise and can result in streak artifacts.…”

Iterative relaxation methods for image reconstruction

“…Some of the other papers mentioning similar methods for image reconstruction are [2,5,6,7,8,10]. Such algorithms are commonly referred to as 17'0 ART (algebraic reconstruction techniques).…”

Ultra - Fast Convolution Approximations for Computerized Tomography

“…After scaling, the plots become near-identical, both exhibiting the rapidly oscillating noise-like error which is characteristic of filters derived from window functions having discontinuities at the cutoff frequency [3]. This ripple artifact or "ringing" is slightly more severe when the approximate filter is used, but it can be effectively suppressed by nonlinear smoothing of the reconstructed image [6]. The additional error due to approximation of the filter would appear to be tolerable in a wide variety of applications, especially those in which the quality of reconstruction is limited by noisy or inconsistent projection data.…”