Loading web-font TeX/Main/Regular
Fast Three-Material Modeling With Triple Arch Projection for Electronic Cleansing in CTC | IEEE Journals & Magazine | IEEE Xplore

Fast Three-Material Modeling With Triple Arch Projection for Electronic Cleansing in CTC


Abstract:

In this paper, we propose a fast three-material modeling for electronic cleansing (EC) in computed tomographic colonography. Using a triple arch projection, our three-mat...Show More

Abstract:

In this paper, we propose a fast three-material modeling for electronic cleansing (EC) in computed tomographic colonography. Using a triple arch projection, our three-material modeling provides a very quick estimate of the three-material fractions to remove ridge-shaped artifacts at the T-junctions where air, soft-tissue (ST), and tagged residues (TRs) meet simultaneously. In our approach, colonic components including air, TR, the layer between air and TR, the layer between ST and TR (L_{\rm ST/TR}), and the T-junction are first segmented. Subsequently, the material fraction of ST for each voxel in L_{\rm ST/TR} and the T-junction is determined. Two-material fractions of the voxels in L_{\rm ST/TR} are derived based on a two-material transition model. On the other hand, three-material fractions of the voxels in the T-junction are estimated based on our fast three-material modeling with triple arch projection. Finally, the CT density value of each voxel is updated based on our fold-preserving reconstruction model. Experimental results using ten clinical datasets demonstrate that the proposed three-material modeling successfully removed the T-junction artifacts and clearly reconstructed the whole colon surface while preserving the submerged folds well. Furthermore, compared with the previous three-material transition model, the proposed three-material modeling resulted in about a five-fold increase in speed with the better preservation of submerged folds and the similar level of cleansing quality in T-junction regions.
Published in: IEEE Transactions on Biomedical Engineering ( Volume: 61, Issue: 7, July 2014)
Page(s): 2102 - 2111
Date of Publication: 26 March 2014

ISSN Information:

PubMed ID: 24686232

Funding Agency:


References

References is not available for this document.