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Image‐based dual energy CT using optimized precorrection functions: A practical new approach of material decomposition in image domain
Author(s) -
Maaß Clemens,
Baer Matthias,
Kachelrieß Marc
Publication year - 2009
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3157235
Subject(s) - digital enhanced cordless telecommunications , scanner , computer science , artificial intelligence , computer vision , image quality , iterative reconstruction , energy (signal processing) , image processing , image (mathematics) , mathematics , telecommunications , statistics , wireless
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.

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