Standardization of blood flow measurements by automated vascular analysis from power Doppler ultrasound scan

Yi Yin; Pádraig Looney; Sally L. Collins

doi:10.1117/12.2549349

16 March 2020 Standardization of blood flow measurements by automated vascular analysis from power Doppler ultrasound scan

Yi Yin, Pádraig Looney, Sally L. Collins

Author Affiliations +

Proceedings Volume 11314, Medical Imaging 2020: Computer-Aided Diagnosis; 113144C (2020) https://doi.org/10.1117/12.2549349
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

Abstract

Power Doppler ultrasound imaging provides a non-invasive method to explore tissue vascularity in real-time. It has farreaching clinical utility, for example to assess the perfusion of organs such as the placenta. In this study, a fully automated method was proposed to standardize the power Doppler signals in the placental bed to estimate the perfusion by a technique known as fractional moving blood volume (FMBV). The uterine vasculature was extracted by a region growing algorithm from 3D power Doppler scan and further localized based on the placenta segmentation obtained by a multi-class fully Convolution Neural Network (CNN). The largest vessel close to the volume of interest (VOI) in placenta was identified within which the average power Doppler signal was used as a standardization value to correct the signal attenuation in placenta bed to estimate the FMBV measurement. This is the first successful attempt to automatically identify individual blood vessel segments from a complex uterine vascular plexus. The proposed method was performed in twenty 3D power Doppler scans of first trimester placenta with promising results. The mean ± STD FMBV value was 21.35% ± 9.43%. With further analysis and evaluation in large dataset, the proposed method will serve as an efficient tool for assessing the blood perfusion in placenta bed.

Citation Download Citation

Yi Yin, Pádraig Looney, and Sally L. Collins "Standardization of blood flow measurements by automated vascular analysis from power Doppler ultrasound scan", Proc. SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 113144C (16 March 2020); https://doi.org/10.1117/12.2549349

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