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Construction Of Finite Element Model Of Human Head In TDCS

Posted on:2019-07-01Degree:MasterType:Thesis
Country:ChinaCandidate:H L LiuFull Text:PDF
GTID:2428330551460055Subject:Detection Technology and Automation
Abstract/Summary:PDF Full Text Request
Transcranial Direct Current Stimulation(TDCS)is an atraumatic and non-invasive technique for human head stimulation.The related researches of TDCS could be divided into clinical experiments and computer modeling simulation analyses.Because of the absolute safety,high efficiency,and low cost,computer simulation is the most frequently used method for studying TDCS.The establishment of a real human head model is the premise and the key to achieving TDCS simulation analysis.This paper introduces the historical development backgroun d,research status,physiological mechanism,basic principles and mathematical models of simulation of TDCS.To establish a finite element model of the head,the premise is that more accurate image segmentations can be done,the electrical conductivity of different human tissues is not the same.By looking up the information and data of head anatomy,combine with the signal characteristics of the main tissues of the head in MR imaging,the segmentation could be determined.There are seven parts,they are s calp,skull,cerebrospinal fluid,gray matter,white matter,air and eyeballs.In the image segmentation section,the head MR data is denoised at first by a non-local mean algorithm,and then the air,eyeballs,skull and scalp are segmented by the Livewire tool in Mimics software.For the brain part,a region growth algorithm with auto seed select and kernel density estimation is used,and the problem of under-segmentation or over-segmentation caused by manually setting the threshold is improved.Finally,b y relevant model quality verification and applicability evaluation,the results show that the head model established in this paper has strong applicability to the simulation research of TDCS.
Keywords/Search Tags:TDCS, Finite element model, Non-local means, Image segmentation, Region grow
PDF Full Text Request
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