國家衛生研究院 NHRI:Item 3990099045/1504
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    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/1504


    Title: An automatic MRI/SPECT registration algorithm using image intensity and anatomical feature as matching characters: application on the evaluation of Parkinson's disease
    Authors: Lee, JD;Huang, CH;Weng, YH;Lin, KJ;Chen, CT
    Contributors: Division of Medical Engineering Research
    Abstract: Single-photon emission computed tomography (SPECT) of dopamine transporters with Tc-99m-TRODAT-1 has recently been proposed to offer valuable information in assessing the functionality of dopaminergic systems. Magnetic resonance imaging (MRI) and SPECT imaging are important in the noninvasive examination of dopamine concentration in vivo. Therefore, this investigation presents an automated MRI/SPECT image registration algorithm based on a new similarity metric. This similarity metric combines anatomical features that are characterized by specific binding, the mean count per voxel in putamens and caudate nuclei, and the distribution of image intensity that is characterized by normalized mutual information (NMI). A preprocess, a novel two-cluster SPECT normalization algorithm, is also presented for MRI/SPECT registration. Clinical MRI/SPECT data from 18 healthy subjects and 13 Parkinson's disease (PD) patients are involved to validate the performance of the proposed algorithms. An appropriate color map, such as "rainbow," for image display enables the two-cluster SPECT normalization algorithm to provide clinically meaningful visual contrast. The proposed registration scheme reduces target registration error from > 7 mm for conventional registration algorithm based on NMI to approximately 4 mm. The error in the specific/nonspecific Tc-99m-TRODAT-1 binding ratio, which is employed as a quantitative measure of TRODAT receptor binding, is also reduced from 0.45 +/- 0.22 to 0.08 +/- 0.06 among healthy subjects and from 0.28 +/- 0.18 to 0.12 +/- 0.09 among PD patients. (c) 2007 Elsevier Inc. All rights reserved.
    Keywords: Radiology, Nuclear Medicine & Medical Imaging
    Date: 2007-05
    Relation: Nuclear Medicine and Biology. 2007 May;34(4):447-457.
    Link to: http://dx.doi.org/10.1016/j.nucmedbio.2007.02.008
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0969-8051&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000246775600013
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=34248219067
    Appears in Collections:[Others] Periodical Articles

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