Material decomposition with prior knowledge aware iterative denoising (MD-PKAID).

Material decomposition with prior knowledge aware iterative denoising (MD-PKAID).
Phys Med Biol. 2018 Aug 23;:
Authors: Tao S, Rajendran K, McCollough CH, Leng S
Abstract
Dual- or multi-energy CT, also known as spectral CT, obtains X-ray attenuation measurements at two or more energy spectra, allowing quantification of materials with different compositions. This process is known as material decomposition, which is the basis for a number of spectral CT applications. The conventional image-domain basis material decomposition is based on a least-squares fitting between the underlying material-specific images and the measured source spectral CT images (i.e., energy-bin or energy-threshold CT images), and a non-iterative solution based on matrix inversion can be derived for this process. However, due to its ill-conditioned nature, the material decomposition process is intrinsically susceptible to noise amplification. Hence, material-specific images can be contaminated by the presence of strong noise, which compromises the conspicuity of small objects, and hinders the delineation of anatomical regions of interest and associated pathology. In this work, we describe an image domain Material Decomposition framework with Prior Knowledge Aware Iterative Denoising (MD-PKAID). The proposed framework exploits the structural redundancy between the individual material-specific images and the source spectral CT images to retain structural details in ...

Source: Physics in Medicine and Biology - August 23, 2018 Category: Physics Authors: Tao S, Rajendran K, McCollough CH, Leng S Tags: Phys Med Biol Source Type: research