While the expenses for computational power decrease, iterative reconstruction methods for x-ray computed tomography (CT) that allow the use of improved model assumptions, become more attractive. In applications for non-destructive testing one of the most common degradations of image quality with standard x-ray CT reconstruction methods is beam hardening. Techniques for beam hardening correction...

Positron emission tomography (PET) scanners collect measurements of a patient’s in vivo radiotracer distribution. These measurements are reconstructed into cross-sectional images. Tomographic image reconstruction forms images of functional information in nuclear medicine applications and the same principles can be applied to modalities such as X-ray computed tomography. This chapter provides a ...

AIM To assess the effect of two iterative reconstruction algorithms (AIDR and AIDR3D) and individualized automatic tube current selection on radiation dose and image quality in computed tomography coronary angiography (CTCA). MATERIALS AND METHODS In a single-centre cohort study, 942 patients underwent electrocardiogram-gated CTCA using a 320-multidetector CT system. Images from group 1 (n = ...

Recently, a number of approaches to low-dose computed tomography (CT) have been developed and deployed in commercialized CT scanners. Tube current reduction is perhaps the most actively explored technology with advanced image reconstruction algorithms. Sparse data sampling is another viable option to the low-dose CT, and sparse-view CT has been particularly of interest among the researchers in ...

Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image rec...

The primal-dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1-26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems for the purpose of designing iterative image reconstruction algorithms for CT. The primal-dual algorithm...

Over the past two decades, rapid system and hardware development of x-ray computed tomography (CT) technologies has been accompanied by equally exciting advances in image reconstruction algorithms. The algorithmic development can generally be classified into three major areas: analytical reconstruction, model-based iterative reconstruction, and application-specific reconstruction. Given the lim...

We have developed an image quality theory for reconstruction that we apply to filtered back-projection (FBP) and statistical reconstruction (OSEM) for Single Photon Emission Computed Tomography (SPECT). Quantitative measures of reconstruction performance are given in terms of signal and noise power spectra, SPS and NPS, that we derive from phantom images. This allows evaluating the properties o...

We have developed an image quality theory for reconstruction that we apply to filtered back-projection (FBP) and statistical reconstruction (OSEM) for Single Photon Emission Computed Tomography (SPECT). Quantitative measures of reconstruction performance are given in terms of signal and noise power spectra, SPS and NPS, that we derive from phantom images. This allows evaluating the properties o...