Metrics for comparison of image dataset and segmentation methods for fractal analysis of retinal vasculature

IF 4.9 2区医学 Q1 ENGINEERING, BIOMEDICAL

Biomedical Signal Processing and Control Pub Date : 2025-02-12 DOI:10.1016/j.bspc.2025.107650

Asmae Igalla El-Youssfi, José Manuel López-Alonso

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引用次数: 0

Abstract

Fractal analysis of images of the retinal vasculature is an instrument that has proven to be of great value both for the characterization of various pathologies and for the study of the vasculature in healthy retinas. To quantify this parameter, it is necessary to consider the treatment of the fractal object and the analysis conditions to ensure the validity of the results. Fractal and multifractal analysis of the retinal vasculature depends on several factors, including the fractal methods applied, the segmentation algorithm and calculation used, and especially the quality of the retinal image which directly influences the accuracy of the segmentation. These factors can influence the calculation and analysis of the fractal or multifractal dimensions. In the present work, different metrics have been developed to quantify the differences introduced by different segmentation methods and image datasets. Using the developed metrics, it has been possible to determine and quantify the influence of the factors studied effectively. The results indicate that the developed metrics allow to quantify these differences, as well as provide criteria on which are the best methods and protocols, which is relevant when using fractal and multifractal methods as an aid in retinal characterization and in the diagnosis of different anomalies.

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来源期刊

Biomedical Signal Processing and Control 工程技术-工程：生物医学

CiteScore

9.80

自引率

13.70%

发文量

822

审稿时长

4 months

期刊介绍： Biomedical Signal Processing and Control aims to provide a cross-disciplinary international forum for the interchange of information on research in the measurement and analysis of signals and images in clinical medicine and the biological sciences. Emphasis is placed on contributions dealing with the practical, applications-led research on the use of methods and devices in clinical diagnosis, patient monitoring and management. Biomedical Signal Processing and Control reflects the main areas in which these methods are being used and developed at the interface of both engineering and clinical science. The scope of the journal is defined to include relevant review papers, technical notes, short communications and letters. Tutorial papers and special issues will also be published.