Med Biol Eng Comput - A hybrid strategy to integrate surface-based and mutual-information-based methods for co-registering brain SPECT and MR images.

Tópicos

{ imag(1057) registr(996) error(939) }
{ method(1557) propos(1049) approach(1037) }
{ imag(2830) propos(1344) filter(1198) }
{ general(901) number(790) one(736) }
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{ method(2212) result(1239) propos(1039) }
{ data(1714) softwar(1251) tool(1186) }
{ howev(809) still(633) remain(590) }
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{ use(1733) differ(960) four(931) }
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{ featur(3375) classif(2383) classifi(1994) }
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{ algorithm(1844) comput(1787) effici(935) }
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{ model(2220) cell(1177) simul(1124) }
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Resumo

Co-registration of brain SPECT and MR images has been used extensively in clinical applications. The complementary features of two major co-registration methods--surface- and mutual-information-based (MI-based)--motivated us to study a hybrid-based scheme that uses the surface-based method to achieve a quick alignment, followed by the MI-based method for fine tuning. Computer simulations were conducted to evaluate the accuracy and robustness of surface-, MI-, and hybrid-based registration methods by designing different levels of noise and mismatch in the registration experiments. Results demonstrated that the hybrid surface-MI-based scheme outperforms both the surface- and MI-based methods in providing superior accuracy and success rates. Specifically, the translational and rotational errors were no more than 1 mm and 2?, respectively, with consistent success rates over 98%. Besides, the hybrid-based method saved 12-53% of the computation efforts, compared with using the MI-based method alone. We recommend the use of hybrid-based method when the orientational differences between the floating and reference images exceed 10?.

Resumo Limpo

coregistr brain spect mr imag use extens clinic applic complementari featur two major coregistr methodssurfac mutualinformationbas mibasedmotiv us studi hybridbas scheme use surfacebas method achiev quick align follow mibas method fine tune comput simul conduct evalu accuraci robust surfac mi hybridbas registr method design differ level nois mismatch registr experi result demonstr hybrid surfacemibas scheme outperform surfac mibas method provid superior accuraci success rate specif translat rotat error mm respect consist success rate besid hybridbas method save comput effort compar use mibas method alon recommend use hybridbas method orient differ float refer imag exceed

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