Image-based dual energy CT using optimized precorrection functions: a practical new approach of material decomposition in image domain.
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.
Maass
Clemens
C
Institute of Medical Physics, University of Erlangen-Nürnberg, Erlangen, Germany. clemens.maass@imp.uni-erlangen.de
Baer
Matthias
M
Kachelriess
Marc
M
D000465:Algorithms; D000818:Animals; D002138:Calibration; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D051379:Mice; D013902:Radiography, Thoracic; D014057:Tomography, X-Ray Computed / Q000379:methods*; D055114:X-Ray Microtomography