Image-domain multimaterial decomposition for dual-energy CT based on prior information of material images
Abstract
PurposeDual-Energy Computed Tomography (DECT) is of great interest in medical imaging, security inspection, and nondestructive testing. Most DECT reconstruction methods focus on producing two material images with different linear attenuation coefficients. However, the ability to reconstruct three or more basis materials is clinically and industrially important. Under the assumption that there are at most three materials in each pixel, there are a few methods that estimate multiple material images from DECT measurements by enforcing sum-to-one and a box constraint ([0 1]) derived from both the volume and mass conservation assumption. The recently proposed image-domain multimaterial decomposition (MMD) method introduces edge-preserving regularization for each material image. It enforces the assumption that there are at most three materials in each pixel using a time-consuming loop over all possible material triplets. However, this method neglects relations among material images. We propose a new image-domain MMD model for DECT that considers the prior information that different material images have common or complementary edges and encourages sparsity of material composition in each pixel using regularization.MethodThe proposed PWLS-TNV-ℓ0 method uses penalized weighted least-square (PWLS) reconstruction with three regularization terms. The first term is total nuclear variation (TNV) that accounts for the image property that basis material images share common or complementary boundaries and each material image is piecewise constant. The second term is an ℓ0 norm that encourages each pixel containing a small subset of material types out of several possible materials. The third term is a characteristic function based on sum-to-one and a box constraint derived from the volume and mass conservation assumption. We apply the Alternating Direction Method of Multipliers (ADMM) to optimize the cost function of the PWLS-TNV-ℓ0 method.ResultWe evaluated the proposed method on a simulated digital phantom, Catphan
- Publication:
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Medical Physics
- Pub Date:
- August 2018
- DOI:
- 10.1002/mp.13001
- arXiv:
- arXiv:1710.07028
- Bibcode:
- 2018MedPh..45.3614D
- Keywords:
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- Physics - Medical Physics;
- Mathematics - Numerical Analysis
- E-Print:
- doi:10.1002/mp.13001