Parallel implementation of the accelerated BEM approach for EMSI of the human brain.
Boundary element method (BEM) is one of the numerical methods which is commonly used to solve the forward problem (FP) of electro-magnetic source imaging with realistic head geometries. Application of BEM generates large systems of linear equations with dense matrices. Generation and solution of the...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 46; no. 7; pp. 671 - 680 |
|---|---|
| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Jul2008
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105560769&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105560769 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jul2008 vid: 46 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105560769 NLM18299914 2010069503 10.1007/s11517-008-0316-0 NLM18299914 105560769 ppf: 671 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Parallel implementation of the accelerated BEM approach for EMSI of the human brain. aug: au: Ataseven Y Akalin-Acar Z Acar CE Gençer NG Ataseven, Y Akalin-Acar, Z Acar, C E Gençer, N G affil: Department of Electrical and Electronics Engineering, Brain Research Laboratory, Middle East Technical University, 06531, Ankara, Turkey sug: subj: Brain Physiology Diagnosis, Neurologic Methods Electroencephalography Methods Algorithms Head Anatomy and Histology Local Area Networks Magnetic Resonance Imaging Models, Anatomic Models, Biological Signal Processing, Computer Assisted Human ab: Boundary element method (BEM) is one of the numerical methods which is commonly used to solve the forward problem (FP) of electro-magnetic source imaging with realistic head geometries. Application of BEM generates large systems of linear equations with dense matrices. Generation and solution of these matrix equations are time and memory consuming. This study presents a relatively cheap and effective solution for parallel implementation of the BEM to reduce the processing times to clinically acceptable values. This is achieved using a parallel cluster of personal computers on a local area network. We used eight workstations and implemented a parallel version of the accelerated BEM approach that distributes the computation and the BEM matrix efficiently to the processors. The performance of the solver is evaluated in terms of the CPU operations and memory usage for different number of processors. Once the transfer matrix is computed, for a 12,294 node mesh, a single FP solution takes 676 ms on a single processor and 72 ms on eight processors. It was observed that workstation clusters are cost effective tools for solving the complex BEM models in a clinically acceptable time. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|