Image-based dual energy CT using optimized precorrection functions: A practical new approach of material decomposition in image domain

Abstract

Dual energy CT (DECT) measures the object of interest using two different x-ray spectra in order to provide energy-selective CT images or in order to get the material decomposition of the object. Today, two decomposition techniques are known. Image-based DECT uses linear combinations of reconstructed images to get an image that contains material-selective DECT information. Rawdata-based DECT correctly treats the available information by passing the rawdata through a decomposition function that uses information from both rawdata sets to create DECT specific (e.g., material-selective) rawdata. Then the image reconstruction yields material-selective images. Rawdata-based image decomposition generally obtains better image quality; however, it needs matched rawdata sets. This means that physically the same lines need to be measured for each spectrum. In today's CT scanners, this is not the case. The authors propose a new image-based method to combine mismatched rawdata sets for DECT information. The method allows for implementation in a scanner's rawdata precorrection pipeline or may be used in image domain. They compare the ability of the three methods (image-based standard method, proposed method, and rawdata-based standard method) to perform material decomposition and to provide monochromatic images. Thereby they use typical clinical and preclinical scanner arrangements including circular cone-beam CT and spiral CT. The proposed method is found to perform better than the image-based standard method and is inferior to the rawdata-based method. However, the proposed method can be used with the frequent case of mismatched data sets that exclude rawdata-based methods.

Complementary contrast media for metal artifact reduction in dual-energy computed tomography

“…New methodologies for noise suppression in the decomposition process are in development, both in projection and image space. [41][42][43] In the future, with reliable material separation and improved quality in these decomposition images, blending them with VMS data may offer a viable alternative to the use of high-Z contrast agents for this task. However, the material decomposition data, which for iodine is highly dependent on the low-kVp projection data, will likely be subject to metal artifacts such as those discussed in this report.…”

Development of a CT scanner based on the Medipix family of detectors

“…[3][4][5][6][7] In addition we analyzed simulation results from our own group, our collaborating partners, and industry.…”

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

“…However this requires projection data which may not be available from a clinical CT scanner as many clinical scanners generate only the reconstructed CT images. 19 Additionally, projection-domain decomposition requires exact angular matching of the projection data, which can be difficult on dual source scanners since data are acquired orthogonally. 5, 21 Here we focus on imagedomain decomposition, which is readily implementable on different CT scanners as a post-reconstruction procedure.…”

“…11,19,20 Decomposition in the projection domain has the advantage of being able to correct for beam-hardening artifacts. However this requires projection data which may not be available from a clinical CT scanner as many clinical scanners generate only the reconstructed CT images.…”