Abstract:
In this paper, we propose an electronic cleansing method using a novel reconstruction model for removing tagged materials (TMs) in computed tomography (CT) images. To add...Show MoreMetadata
Abstract:
In this paper, we propose an electronic cleansing method using a novel reconstruction model for removing tagged materials (TMs) in computed tomography (CT) images. To address the partial volume (PV) and pseudoenhancement (PEH) effects concurrently, material fractions and structural responses are integrated into a single reconstruction model. In our approach, colonic components including air, TM, an interface layer between air and TM, and an interface layer between soft-tissue (ST) and TM (ILST/TM ) are first segmented. For each voxel in ILST/TM, the material fractions of ST and TM are derived using a two-material transition model, and the structural response to identify the folds submerged in the TM is calculated by the rut-enhancement function based on the eigenvalue signatures of the Hessian matrix. Then, the CT density value of each voxel in ILST/TM is reconstructed based on both the material fractions and structural responses. The material fractions remove the aliasing artifacts caused by a PV effect in ILST/TM effectively while the structural responses avoid the erroneous cleansing of the submerged folds caused by the PEH effect. Experimental results using ten clinical datasets demonstrated that the proposed method showed higher cleansing quality and better preservation of submerged folds than the previous method, which was validated by the higher mean density values and fold preservation rates for manually segmented fold regions.
Published in: IEEE Transactions on Biomedical Engineering ( Volume: 60, Issue: 6, June 2013)