Diameter Estimation of Fallopian Tubes Using Visual Sensing

Calculating an accurate diameter of arbitrary vessel-like shapes from 2D images is great use in various applications within medical and biomedical fields. Understanding the changes morphological dimensioning biological vessels provides a better understanding their properties functionality. Estimating tubes very challenging as dimensions change continuously along its length. This paper describes novel algorithm that estimates with changing cross-section. The algorithm, evaluated using controlled images, automated estimation higher accuracy than manual measurements precise information about diametrical tube. It demonstrated more results much shorter time. methodology has potential to speed up diagnostic procedures wide range