2020/01/01 by Saba Adabi, Siavash Ghavami, Adabi, Saba +5
Engineering · Medicine · #FOS: Electrical engineering #FOS: Physical sciences #Image and Video Processing (eess.IV) #Medical Physics (physics.med-ph) #Photoacoustic and Ultrasonic Imaging #Ultrasound Imaging and Elastography #Ultrasound and Hyperthermia Applications #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2011.02096
openalex publication_date 2020/11/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Vascular networks can provide invaluable information about tumor\nangiogenesis. Ultrafast Doppler imaging enables ultrasound to image\nmicro-vessels by applying tissue clutter filtering methods on the\nSpatio-temporal data obtained from plane-wave imaging. However, motion is an\nintrinsic part of microvasculature imaging due to various reasons e.g breathing\nand vessel pulsation. Part of such a motion is taken care of by using\nSpatio-temporal cluttering filtering. Nonetheless, the remaining part of the\nmotion who manifests itself as blurring or generating ghost vessels should be\ncorrected using another level of motion compensation. We proposed a robust and\ncomputationally efficient motion compensation algorithm for Ultrasound\nmicro-vessel imaging. We successfully evaluated the performance of the\nalgorithm by a simulation study. Finally, we tested the proposed motion\ncompensation method on the in vivo data of microvasculature in different organs\nincluding breast and thyroid. Results show blurring and ghost vessel problems\nare significantly reduced using the proposed algorithm. Moreover, our\nquantitative assessment demonstrated that image correlation among different\nframes in Ultrafast Doppler imaging is significantly improved utilizing the\nproposed motion correction method.\n