Using Edge-Preserving Algorithm with Non-local Mean for Significantly Improved Image-Domain Material Decomposition in Dual Energy CT
| Autor: | Zhao, Wei, Niu, Tianye, Xing, Lei, Xie, Yaoqin, Xiong, Guanglei, Elmore, Kimberly, Zhu, Jun, Wang, Luyao, Min, James K. |
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| Rok vydání: | 2016 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1088/0031-9155/61/3/1332 |
| Popis: | Increased noise is a general concern for dual-energy material decomposition. Here, we develop an image-domain material decomposition algorithm for dual-energy CT (DECT) by incorporating an edge-preserving filter into the Local HighlY constrained backPRojection Reconstruction (HYPR-LR) framework. With effective use of the non-local mean, the proposed algorithm, which is referred to as HYPR-NLM, reduces the noise in dual energy decomposition while preserving the accuracy of quantitative measurement and spatial resolution of the material-specific dual energy images. We demonstrate the noise reduction and resolution preservation of the algorithm with iodine concentrate numerical phantom by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). We also show the superior performance of the HYPR-NLM over the existing methods by using two sets of cardiac perfusing imaging data. The reference drawn from the comparison study includes: (1) HYPR-NLM significantly reduces the DECT material decomposition noise while preserving quantitative measurements and high-frequency edge information, and (2) HYPR-NLM is robust with respect to parameter selection. Comment: 23 pages, 11 figures. Accepted by Physics in Medicine and Biology |
| Databáze: | arXiv |
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