Mechanical Innovation and Tribology Group, Department of Mechanical Engineering, School of Engineering, University of Birmingham, Birmingham B15 2TT, UK.
Biosensors (Basel). 2021 Apr 1;11(4):100. doi: 10.3390/bios11040100.
Calculating an accurate diameter of arbitrary vessel-like shapes from 2D images is of great use in various applications within medical and biomedical fields. Understanding the changes in morphological dimensioning of the biological vessels provides a better understanding of their properties and functionality. Estimating the diameter of the tubes is very challenging as the dimensions change continuously along its length. This paper describes a novel algorithm that estimates the diameter of biological tubes with a continuously changing cross-section. The algorithm, evaluated using various controlled images, provides an automated diameter estimation with higher and better accuracy than manual measurements and provides precise information about the diametrical changes along the tube. It is demonstrated that the automated algorithm provides more accurate results in a much shorter time. This methodology has the potential to speed up diagnostic procedures in a wide range of medical fields.
从二维图像中计算任意类容器形状的精确直径，在医学和生物医学领域的各种应用中非常有用。了解生物血管形态尺寸的变化可以更好地理解它们的特性和功能。由于管的尺寸沿着其长度连续变化，因此估计管的直径极具挑战性。本文描述了一种新的算法，用于估计具有连续变化的横截面的生物管的直径。该算法通过使用各种受控图像进行评估，提供了比手动测量更高和更好的自动直径估计，并提供了关于管内直径变化的精确信息。结果表明，自动化算法在更短的时间内提供了更准确的结果。这种方法有可能在广泛的医学领域加快诊断程序。
