Fast model-based X-ray CT reconstruction using spatially nonhomogeneous ICD optimization

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Zhou YuJiang Hsieh

Abstract

Recent applications of model-based iterative reconstruction (MBIR) algorithms to multislice helical CT reconstructions have shown that MBIR can greatly improve image quality by increasing resolution as well as reducing noise and some artifacts. However, high computational cost and long reconstruction times remain as a barrier to the use of MBIR in practical applications. Among the various iterative methods that have been studied for MBIR, iterative coordinate descent (ICD) has been found to have relatively low overall computational requirements due to its fast convergence. This paper presents a fast model-based iterative reconstruction algorithm using spatially nonhomogeneous ICD (NH-ICD) optimization. The NH-ICD algorithm speeds up convergence by focusing computation where it is most needed. The NH-ICD algorithm has a mechanism that adaptively selects voxels for update. First, a voxel selection criterion VSC determines the voxels in greatest need of update. Then a voxel selection algorithm VSA selects the order of successive voxel updates based upon the need for repeated updates of some locations, while retaining characteristics for global convergence. In order to speed up each voxel update, we also propose a fast 1-D optimiza...Continue Reading

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Citations

Oct 10, 2008·Medical Physics·Johan Sunnegårdh, Per-Erik Danielsson
Jun 1, 2014·Medical Physics·Xing ZhangXiaojun Liu
Aug 31, 2013·The International Journal of Cardiovascular Imaging·Stefan B PuchnerChristopher L Schlett
Apr 10, 2014·Academic Radiology·Masahiro YanagawaNoriyuki Tomiyama
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Dec 2, 2014·IEEE Transactions on Medical Imaging·Guobao Wang, Jinyi Qi
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Sep 24, 2013·IEEE Transactions on Medical Imaging·Ruoqiao ZhangJiang Hsieh

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