Novel Computerized Method for Measurement of Retinal Vessel Diameters
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Published on: May 19, 2023
Hichem Guedri1, Mariem Ben Abdallah2, Fraj Echouchene3
1Electronics and Microelectronics Laboratory, Physics Department, Faculty of Sciences, Monastir University, Monastir 5019, Tunisia. himougu@yahoo.fr.
Insights
This study introduces a new computer algorithm for accurately measuring human retinal blood vessel diameter. The method improves upon manual techniques, offering faster and more reliable detection of vascular changes linked to eye diseases.
Area of Science:
- Ophthalmology
- Medical Imaging
- Biomedical Engineering
Background:
- Alterations in human retinal blood vessel topology are linked to diseases like diabetic retinopathy, hypertensive retinopathy, and macular degeneration.
- Current methods for detecting these vascular changes are often slow, have gaps, and are prone to human bias.
Purpose of the Study:
- To present and investigate a novel computer-based method for accurately measuring blood vessel diameter in retinal images.
- To overcome the limitations of manual detection methods in identifying retinal vascular changes.
Main Methods:
- The proposed method involves thresholding segmentation and thinning.
- Characteristic points are determined using the Douglas-Peucker algorithm.
- Active contours are employed for vessel contour detection, and Heron's Formula calculates vessel diameter.
Main Results:
- The novel method was tested on six sample retinal images.
- The results demonstrated fewer errors compared to existing techniques.
- The findings confirm the high performance and accuracy of the proposed method.
Conclusions:
- The developed algorithm provides a faster and more accurate alternative to manual methods for measuring retinal blood vessel diameter.
- This technique has the potential to improve the early detection and monitoring of various retinal diseases.
Abstract:
Several clinical studies reveal the relationship between alterations in the topologies of the human retinal blood vessel, the outcrop and the disease evolution, such as diabetic retinopathy, hypertensive retinopathy, and macular degeneration. Indeed, the detection of these vascular changes always has gaps. In addition, the manual steps are slow, which may be subjected to a bias of the perceiver. However, we can overcome these troubles using computer algorithms that are quicker and more accurate. This paper presents and investigates a novel method for measuring the blood vessel diameter in the retinal image. The proposed method is based on a thresholding segmentation and thinning step, followed by the characteristic point determination step by the Douglas-Peucker algorithm. Thereafter, it uses the active contours to detect vessel contour. Finally, Heron's Formula is applied to assure the calculation of vessel diameter. The obtained results for six sample images showed that the proposed method generated less errors compared to other techniques, which confirms the high performance of the proposed method.
