Overcoming Nonlinear Partial Volume Effects in Known-Component Reconstruction of Cochlear Implants.
Overcoming Nonlinear Partial Volume Effects in Known-Component Reconstruction of Cochlear Implants.
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DOI：
10.1117/12.2007945
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Siewerdsen JH
中科院分区：
文献类型：
--
作者：
Stayman JW;Dang H;Otake Y;Zbijewski W;Noble J;Dawant B;Labadie R;Carey JP;Siewerdsen JH
Nonlinear partial volume (NLPV) effects can be significant for objects with large attenuation differences and fine detail structures near the spatial resolution limits of a tomographic system. This is particularly true for small metal devices like cochlear implants. While traditional model-based approaches might alleviate these artifacts through very fine sampling of the image volume and subsampling of rays to each detector element, such solutions can be extremely burdensome in terms of memory and computational requirements. The work presented in this paper leverages the model-based approach called “known-component reconstruction” (KCR) where prior knowledge of a surgical device is integrated into the estimation. In KCR, the parameterization of the object separates the volume into an unknown background anatomy and a known component with unknown registration. Thus, one can model projections of an implant at very high spatial resolution while limiting the spatial resolution of the anatomy - in effect, modeling NLPV effects where they are most significant. We present modifications of the KCR approach that can be used to largely eliminate NLPV artifacts, and demonstrate the efficacy of the modified technique (with improved image quality and accurate implant position estimates) for the cochlear implant imaging scenario.
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影响因子：
3.5
作者：
JOSEPH, PM;SPITAL, RD
通讯作者：
SPITAL, RD
DOI：
10.1007/s101620020013
发表时间：
2002-09-01
影响因子：
2.4
作者：
Skinner, MW;Ketten, DR;Blocker, B
通讯作者：
Blocker, B
影响因子：
1.8
作者：
Hsieh, JA
通讯作者：
Hsieh, JA
影响因子：
3.8
作者：
GLOVER, GH;PELC, NJ
通讯作者：
PELC, NJ
影响因子：
10.6
作者：
Long Y;Fessler JA;Balter JM
通讯作者：
Balter JM