China
Africa
Explore chapters and articles related to this topic
Reconstruction from Projections
Published in Stuart R. Stock, MicroComputed Tomography, 2019
ART is an iterative approach to reconstruction, that is, a mathematical trail-and-error approach. Iterative algorithms can be deterministic; examples include ART, simultaneous iterative reconstruction technique (SIRT), and simultaneous algebraic reconstruction technique (SART). Stochastic iterative approaches are a second group, and an example is the maximum likelihood (ML) method. Both deterministic and stochastic iterative algorithms are particularly suited for incorporating prior knowledge about the specimen or for accommodating incomplete data such as significant angular gaps in the series of projections available for reconstruction. It used to be that iterative methods were rarely used because of computational cost and delay but, with the ever-increasing computational power, including graphic processing units (GPU), the iterative methods are gaining in popularity. Techniques beyond ART (SART, ML) are described briefly at the end of this section.
X-ray computed tomography
Published in Elaine DiMasi, Laurie B. Gower, Biomineralization Sourcebook, 2014
Xianghui Xiao, Stuart R. Stock
to obtain CT reconstruction of the spatial distribution of the linear attenuation coe cient (absorption contrast), refractive index (phase contrast), crystallographic structure (diffraction contrast), elemental distribution ( fluorescence contrast), particle size and shape (scattering contrast), and local bonding structure (spectroscopy contrast). In this section, the focus will only be on absorption contrast and on phase contrast. 15.2.2 PRINCIPLES OF COMPUTED TOMOGRAPHY CT reconstructs slices of a specimen digitally from the projections of the specimen along different directions. One CT reconstruction algorithm is called the algebraic reconstruction technique (ART) and is based on a model of CT problem consisting of a system of linear equations (Kak and Slaney 2001). Intuitively, it is easy to understand CT principles from the ART point of view. In the case of absorption contrast imaging, shadow images of a specimen are recorded. The intensity uctuation in a shadow image is due to the specimen attenuation of the incident x-ray, which can be expressed by Beer's law: I = I 0 exp[ µ ( r ) dt ], l
in vivo transit dosimetry
Published in Ross I. Berbeco, Beam’s Eye View Imaging in Radiation Oncology, 2017
ART is resource intensive because it requires a replanning process necessitating additional use of planning equipment and staff time. Furthermore, any adaptation of a plan also requires an additional patient-specific verification, either with a phantom measurement before the next fraction is delivered or in vivo during that fraction, thus further increasing the workload.
Total Variation (TV) l1 Norm Minimization Based Limited Data X-ray CT Image Reconstruction
Published in Research in Nondestructive Evaluation, 2020
Shubhabrata Sarkar, Pankaj Wahi, Prabhat Munshi
A very common method for limited data CT image reconstruction is the Algebraic Reconstruction Technique (ART). ART has been used by Hounsfield [15] in his initial work on tomography. Gordon [16] further enhanced the performance of ART by using multiplicative correction term, and the technique is known as Multiplicative ART or MART. A robust version of MART has been proposed by Mishra et al. [17]. One major drawback of ART is the high computational cost. Bajpai et al. [18] have introduced a new scheme of MART by the application of parallel computing to cut the computational time. Simultaneous Iterative Reconstruction Technique (SIRT) is also a well-known method for handling the limited data CT problem [19]. SIRT is also a highly time-consuming method. The Projections on to Convex Set (POCS) methods fails to produce satisfactory images when there are no suitable constraints in the domain [20].