Comput Math Methods Med - A 3D finite-difference BiCG iterative solver with the Fourier-Jacobi preconditioner for the anisotropic EIT/EEG forward problem.

Tópicos

{ problem(2511) optim(1539) algorithm(950) }
{ take(945) account(800) differ(722) }
{ algorithm(1844) comput(1787) effici(935) }
{ activ(1138) subject(705) human(624) }
{ featur(3375) classif(2383) classifi(1994) }
{ learn(2355) train(1041) set(1003) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ method(984) reconstruct(947) comput(926) }
{ perform(999) metric(946) measur(919) }
{ system(1050) medic(1026) inform(1018) }
{ model(3480) simul(1196) paramet(876) }
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{ data(2317) use(1299) case(1017) }
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{ health(1844) social(1437) communiti(874) }
{ high(1669) rate(1365) level(1280) }
{ method(2212) result(1239) propos(1039) }
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{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
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{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
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{ age(1611) year(1155) adult(843) }
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{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

The Electrical Impedance Tomography (EIT) and electroencephalography (EEG) forward problems in anisotropic inhomogeneous media like the human head belongs to the class of the three-dimensional boundary value problems for elliptic equations with mixed derivatives. We introduce and explore the performance of several new promising numerical techniques, which seem to be more suitable for solving these problems. The proposed numerical schemes combine the fictitious domain approach together with the finite-difference method and the optimally preconditioned Conjugate Gradient- (CG-) type iterative method for treatment of the discrete model. The numerical scheme includes the standard operations of summation and multiplication of sparse matrices and vector, as well as FFT, making it easy to implement and eligible for the effective parallel implementation. Some typical use cases for the EIT/EEG problems are considered demonstrating high efficiency of the proposed numerical technique.

Resumo Limpo

electr imped tomographi eit electroencephalographi eeg forward problem anisotrop inhomogen media like human head belong class threedimension boundari valu problem ellipt equat mix deriv introduc explor perform sever new promis numer techniqu seem suitabl solv problem propos numer scheme combin fictiti domain approach togeth finitediffer method optim precondit conjug gradient cg type iter method treatment discret model numer scheme includ standard oper summat multipl spars matric vector well fft make easi implement elig effect parallel implement typic use case eiteeg problem consid demonstr high effici propos numer techniqu

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