In Vivo 3-D Vector Velocity Estimation with Continuous Data

Simon Holbek, Michael Johannes Pihl, Caroline Ewertsen, Michael Bachmann Nielsen, Jørgen Arendt Jensen

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    590 Downloads (Pure)

    Abstract

    In this study, a method for estimating 3-D vector velocities at very high frame rate using continuous data acquisition is presented. An emission sequence was designed to acquire real-time continuous data in one plane. The transverse oscillation (TO) method was used to estimate 3-D vector flow in a carotid flow phantom and in vivo in the common carotid artery of a healthy 27-year old female. Based on the out-of-plane velocity component during four periodic cycles, estimated flow rates in an experimental setup was 2.96 ml/s ± 0.35 ml/s compared to the expected 3.06 ml/s ± 0.09 ml/s. In the in vivo measurements, three heart cycles acquired at 2.1 kHz showed peak out-of-plane velocities of 83 cm/s, 87 cm/s and 90 cm/s in agreement with the 92 cm/s found with spectral Doppler. Mean flow rate was estimated to 257 ml/min. The results demonstrate that accurate real-time 3- D vector velocities can be obtained using the TO method, which can be used to improve operator-independece when examining blood flow in vivo, thereby increasing accuracy and consistency.
    Original languageEnglish
    Title of host publicationProceedings of IEEE International Ultrasonics Symposium
    Number of pages4
    PublisherIEEE
    Publication date2015
    DOIs
    Publication statusPublished - 2015
    Event2015 IEEE International Ultrasonics Symposium - Taipei, Taiwan, Province of China
    Duration: 21 Oct 201524 Oct 2015
    https://ieeexplore.ieee.org/xpl/conhome/7315052/proceeding

    Conference

    Conference2015 IEEE International Ultrasonics Symposium
    Country/TerritoryTaiwan, Province of China
    CityTaipei
    Period21/10/201524/10/2015
    Internet address

    Fingerprint

    Dive into the research topics of 'In Vivo 3-D Vector Velocity Estimation with Continuous Data'. Together they form a unique fingerprint.

    Cite this