Difference between revisions of "Retina Image Analysis"
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''Tortuosity measurement :'' | ''Tortuosity measurement :'' | ||
| − | We used the density factor (called DF) | + | 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] | [insérer ici la formule] | ||
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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. | 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'' | + | '''Intermediate results''' |
| + | First, we had to plot for one fundus image the blood vessels and adapt the diameter. | ||
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'''Challenge''' | '''Challenge''' | ||
Revision as of 22:51, 12 April 2021
- Project name: Retina Image Analysis
- Tutor: Michael Beyeler (michael [dot] beyeler [at] unil [dot] ch)
- Slides: File:Retina image analysis.pptx
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
