Abstract
The most popular method for assessment the endothelial function, called flow-mediated dilation, is based on monitoring how the brachial artery diameter changes in hyperemia state. All of the existing methods that assess FMD are exceedingly time consuming, as they require supervising analysis of the whole video. The presented method fully-automatically analyzes the videos and returns the FMD value using region of interest (ROI) defined by the operator. The main contributions of this paper are: minimizing inter and intra-observer variability; eliminating supervision from the analysis; applying more informative techniques than edge detectors; providing dataset which can be used by other researchers to test their fully-automatic methods.
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Acknowledgement
Dataset used in this paper was acquired from Jagiellonian Centre for Experimental Therapeutics (JCET) at Jagiellonian University in Kraków, Poland. The ultrasound videos were obtained during the study supported by European Union from the resources of the European Regional Development Fund under the Innovative Economy Programme (grant coordinated by JCET-UJ, No POIG. 01.01.02-00-069/09). We gratefully acknowledge the support from Prof. Stefan Chłopicki that were instrumental to carry out this study.
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Appendix: Code and dataset
Appendix: Code and dataset
The code of application and dataset used in experiment are publicly available under the following link: www.ii.uj.edu.pl/~zielinsb.
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Zieliński, B., Dróżdż, A., Frołow, M. (2016). Fully-Automatic Method for Assessment of Flow-Mediated Dilation. In: Chmielewski, L., Datta, A., Kozera, R., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2016. Lecture Notes in Computer Science(), vol 9972. Springer, Cham. https://doi.org/10.1007/978-3-319-46418-3_39
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