Blood vessels tracking and diameter estimation using Gaussian process

Tracking and diameter estimation of blood vessels using Gaussian process and Radon transform

Tracking and diameter estimation of blood vessels using Gaussian process and Radon transform
keywords: retinal segmentation, blood vessel tracking, Gaussian process, Radon transform, vascular bifurcation detection, diameter estimation

This script track center points and diameter of blood vessels, which is an ongoing challenge in medical image analysis. We hypothesize that the curvature and the diameter of blood vessels are Gaussian processes (GPs). Local Radon transform, which is robust against noise, is subsequently used to compute the features and train the GPs. By learning the kernelized covariance matrix from training data, vessel direction and its diameter are estimated. In order to detect bifurcations, multiple GPs are used and the difference between their corresponding predicted directions is quantified.

References: Masoud Elhami Asl, et al. "Tracking and diameter estimation of retinal vessels using Gaussian process and Radon transform." Journal of Medical Imaging 4.3 (2017): 034006.

This algorithm is the result of many hours of work and problem solving. Please cite the above paper in case you find the script useful in your own research.

Developed and Copyrighted by Masoud Elhami Asl (2017)