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Titolo:
Robust image registration for functional magnetic resonance imaging of thebrain
Autore:
Hsu, CC; Wu, MT; Lee, C;
Indirizzi:
Natl Sun Yat Sen Univ, Dept Comp Sci & Engn, Kaohsiung 80424, Taiwan Natl Sun Yat Sen Univ Kaohsiung Taiwan 80424 gn, Kaohsiung 80424, Taiwan Yung Ta Inst Technol & Commerce, Pingtung, Taiwan Yung Ta Inst Technol & Commerce Pingtung Taiwan merce, Pingtung, Taiwan Kaohsiung Vet Gen Hosp, Dept Radiol, Kaohsiung, Taiwan Kaohsiung Vet Gen Hosp Kaohsiung Taiwan Dept Radiol, Kaohsiung, Taiwan
Titolo Testata:
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
fascicolo: 5, volume: 39, anno: 2001,
pagine: 517 - 524
SICI:
0140-0118(200109)39:5<517:RIRFFM>2.0.ZU;2-1
Fonte:
ISI
Lingua:
ENG
Soggetto:
VOXEL SIMILARITY MEASURES; GEOMETRICAL FEATURES; MUTUAL INFORMATION; MR-IMAGES; MAXIMIZATION; OPTIMIZATION; ALGORITHM; ARTIFACTS;
Keywords:
image registration; robust estimation; functional MR imaging;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Engineering, Computing & Technology
Citazioni:
30
Recensione:
Indirizzi per estratti:
Indirizzo: Lee, C Natl Sun Yat Sen Univ, Dept Comp Sci & Engn, Kaohsiung 80424, Taiwan Natl Sun Yat Sen Univ Kaohsiung Taiwan 80424 hsiung 80424, Taiwan
Citazione:
C.C. Hsu et al., "Robust image registration for functional magnetic resonance imaging of thebrain", MED BIO E C, 39(5), 2001, pp. 517-524

Abstract

Motion-related artifacts are still a major problem in data analysis of functional magnetic resonance imaging (FMRI) studies of brain activation. However, the traditional image registration algorithm is prone to inaccuracy when there are residual variations owing to counting statistics, partial volume effects or biological variation. In particular, susceptibility artifactsusually result in remarkable signal intensity variance, and they can mislead the estimation of motion parameters. In this study, Two robust estimation algorithms for the registration of FMRI images are described. The first estimation algorithm was based on the Newton method and used Tukey's biweight objective function. The second estimation algorithm was based on the Levenberg-Marquardt technique and used a skipped mean objective function. The robust M-estimators can suppress the effects of the outliers by scaling downtheir error magnitudes or completely rejecting outliers using a weighting function. The proposed registration methods consisted of the following steps: fast segmentation of the brain region from noisy background as a preprocessing step; pre-registration of the volume centroids to provide a good initial estimation; and two robust estimation algorithms and a voxel sampling technique to find the affine transformation parameters. The accuracy of thealgorithms was within 0.5 mm in translation and within 0.5 degrees in rotation. For the FMRI data sets, the performance of the algorithms was visually compared with the AIR 2.0 software, which is a software for image registration, using colour-coded statistical mapping by the Kolmogorov-Smirov method. Experimental results showed, that the algorithms provided significant improvement in correcting motion-related artifacts and can enhance the detection of real brain activation.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 28/03/20 alle ore 13:59:10