Non-invasive fiber tracking on diffusion tensor MRI using high-temperature superconducting tape RF coil

In Tsang Lin*, Hong Chang Yang, Li Wei Kuo, Chang Wei Hsieh, Ching Yao, Wei Hao Chang, Chiou Ju Chen, Jyh Horng Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

High-temperature superconducting (HTS) coil is one of the best ways to increase the signal-to-noise ratio (SNR). Bi2Sr2Ca2Cu3Ox (Bi-2223) tapes were suitable to use because of the easier fabrications and lower cost. In this study, we built HTS Bi-2223 tape coils and demonstrated that the SNR of using the HTS tape coil was 3 or 4 folds higher than that of the traditional copper coil for a rat brain MR study. Acquisition time of MR diffusion tensor imaging (DTI) can be reduced by factor of 9 for the same signal-to-noise. Accuracy of fiber tracking using DTI is also significantly improved by a factor of 2.5 or so using HTS coil. In summary, with this HTSC system, a 3T MR system could reach the high signal-to-noise of 12 T MR system with the advantage of less T2 shortening effects at high field. Currents researches are focused on brain connectivity and fMRI studies.

Original languageEnglish
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Pages2329-2332
Number of pages4
Publication statusPublished - 2005
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: 2005 Sept 12005 Sept 4

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume7 VOLS
ISSN (Print)0589-1019

Other

Other2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Country/TerritoryChina
CityShanghai
Period2005/09/012005/09/04

Keywords

  • Bi-2223
  • DTI
  • HTS

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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