A Dynamic System for Tracking Biopsy Needle in Two Dimensional Ultrasound Images

ALSBEIH, Dima, DOUAD, Mohammad I, AL-TAMIMI, Abdel-Karim and AL-JARRAH, Mohammad A (2020). A Dynamic System for Tracking Biopsy Needle in Two Dimensional Ultrasound Images. In: 2020 IEEE 5th Middle East and Africa Conference on Biomedical Engineering (MECBME). IEEE.

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Official URL: https://ieeexplore.ieee.org/document/9265166
Link to published version:: https://doi.org/10.1109/mecbme47393.2020.9265166
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    Abstract

    Ultrasound imaging is widely used to track needle insertion during biopsy surgical procedures. However, the task of tracking the needle tip in ultrasound images is a challenging task that depends on the experience of the physician. To address this limitation, we present different tracking algorithms based on the Kalman filter and particle filter to achieve effective needle tip tracking during biopsy needle insertion procedures. The results showed that the Kalman filter can achieve effective needle tip tracking with an average ± standard deviation error of 1.46 ± 0.92 mm. In comparison, the particle filter can track the needle tip with an average ± standard deviation error of 1.17 ± 0.88 mm when the number of particles is set to 3000.

    Item Type: Book Section
    Additional Information: 2020 IEEE 5th Middle East and Africa Conference on Biomedical Engineering (MECBME)27-29 October 2020, Amman, Jordan. Series ISSN: 2165-4247 © 2020 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Identification Number: https://doi.org/10.1109/mecbme47393.2020.9265166
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 24 Nov 2022 15:11
    Last Modified: 24 Nov 2022 15:11
    URI: https://shura.shu.ac.uk/id/eprint/31047

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