Enhancing flow-mediated dilation analysis by optimizing an open-source software with automated edge detection-Reference-Cited by-同舟云学术

Enhancing flow-mediated dilation analysis by optimizing an open-source software with automated edge detection

Published:2024-08-01 Issue:2 Volume:137 Page:300-311
ISSN:8750-7587
Container-title:Journal of Applied Physiology
language:en
Short-container-title:Journal of Applied Physiology

Author:

Masterova Kseniya S.¹²^ORCID,Wang Jiefei³^ORCID,Mack Courtney²^ORCID,Moro Tatiana⁴^ORCID,Deer Rachel⁵^ORCID,Volpi Elena⁶⁷^ORCID

Affiliation:

1. Graduate School of Biomedical Sciences, University of Texas Medical Branch, Galveston, Texas, United States

2. John Sealy School of Medicine, University of Texas Medical Branch, Galveston, Texas, United States

3. Department of Biostatistics, University of Texas Medical Branch, Galveston, Texas, United States

4. Department of Biomedical Science, University of Padova, Padua, Italy

5. Center for Recovery, Physical Activity, and Nutrition, University of Texas Medical Branch, Galveston, Texas, United States

6. Sealy Center on Aging, University of Texas Medical Branch, Galveston, Texas, United States

7. Barshop Institute, University of Texas Health Science Center San Antonio, San Antonio, Texas, United States

Abstract

This study improves edge detection capabilities and implements noise reduction strategies to optimize an existing open-source software’s suitability for flow-mediated dilation (FMD) analysis. The modified software improves the precision and reliability of FMD analysis compared with the original software algorithm. We demonstrate that this modified open-source software is a robust tool for FMD analysis.

Funder

HHS | NIH | National Center for Advancing Translational Sciences

HHS | NIH | National Institute on Aging

Publisher

American Physiological Society

Link

https://journals.physiology.org/doi/pdf/10.1152/japplphysiol.00063.2023

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