Retina Image Analysis

Revision as of 21:51, 12 April 2021 by Sbprm2021 4 (talk | contribs)
  • Project name: Retina Image Analysis
  • Tutor: Michael Beyeler (michael [dot] beyeler [at] unil [dot] ch)

Intermediary report

                                   Retina Image Analysis                                        
                       Participant : Alexandre Jann, Maylis Touya, Paola Zanchi
                                 Teaching Assistant:  Michael Balayer

Aim

We wanted to know if we can link tortuosity of the blood vessel in the eyes with cardiovascular diseases by using programming and bioinformatics.

Why is this project interesting?

This project is quite interesting because it allows us to have a mathematical insight into the determination of diseases and comorbidity risks. Moreover, since an eye fundus is a less invasive physical exam, allowing us to see well the conditions of the blood vessels in a very short amount of time, it seems that it can be a very good exam, and maybe can replace the actuals vascular exams that are invasive and take a long time to be made.

Method

ARIA

It is a software originally used for measuring the tortuosity of a plant's roots. In fact, ARIA stands for Automatic Root Image Analysis, and has been shown at first in this paper. Here, it has been used to measure the tortuosity of blood vessels in fundus images.

Tortuosity measurement :

We used the density factor (called DF) to calculate the tortuosity of the blood vessels. It consists of the ratio between the length of a line and the length between its first and last point.

[insérer ici la formule]

Statistical tools :

We used the quantile method to determine the outliers of our DF: all the DFs that were above the 3rd quantile were set as irrelevant.

Intermediate results

First, we had to plot for one fundus image the blood vessels and adapt the diameter.


Challenge