Implementation of high-temperature superconducting tapes RF coils for 3T MRI system

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

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

    Abstract

    One way to reduce receiving coil noise in MRI scans is using non-resistive high-temperature superconducting (HTS) coils [1]. They show advantages of much lower cost and easier fabrication over HTS thin film coils. In this work, we built a 200mm in diameter Bi2Sr2Ca2Cu 3O5 (Bi-2223) tape HTS RF coil and demonstrated that the SNR of using the HTS tape coil was 2.22 folds higher than that of the traditional copper coil for a phantom MR study. Test results were in agreement with predictions, and the error of predicted SNR gains and measured SNR gains is about 0.9%. The HTS coil can be expected to generate higher SNR gain after optimization. In the future, in-vivo experiments will be conducted to farther test the capability of the HTS tape coil. Further applications functional MRI is under investigation to test the power of this HTSC system in our 3T system.

    Original languageEnglish
    Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
    Pages7413-7416
    Number of pages4
    Publication statusPublished - 2005 Dec 1
    Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
    Duration: 2005 Sep 12005 Sep 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
    CountryChina
    CityShanghai
    Period2005/09/012005/09/04

    Keywords

    • Bi-2223
    • HTS
    • MRI

    ASJC Scopus subject areas

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

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