Robust approach to ocular fundus image analysis

Guido Tascini; Giorgio Passerini; Paolo Puliti; Primo Zingaretti

doi:10.1117/12.148676

29 July 1993 Robust approach to ocular fundus image analysis

Guido Tascini, Giorgio Passerini, Paolo Puliti, Primo Zingaretti

Proceedings Volume 1905, Biomedical Image Processing and Biomedical Visualization; (1993) https://doi.org/10.1117/12.148676
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States

Abstract

The analysis of morphological and structural modifications of retinal blood vessels plays an important role both to establish the presence of some systemic diseases as hypertension and diabetes and to study their course. The paper describes a robust set of techniques developed to quantitatively evaluate morphometric aspects of the ocular fundus vascular and micro vascular network. They are defined: (1) the concept of 'Local Direction of a vessel' (LD); (2) a special form of edge detection, named Signed Edge Detection (SED), which uses LD to choose the convolution kernel in the edge detection process and is able to distinguish between the left or the right vessel edge; (3) an iterative tracking (IT) method. The developed techniques use intensively both LD and SED in: (a) the automatic detection of number, position and size of blood vessels departing from the optical papilla; (b) the tracking of body and edges of the vessels; (c) the recognition of vessel branches and crossings; (d) the extraction of a set of features as blood vessel length and average diameter, arteries and arterioles tortuosity, crossing position and angle between two vessels. The algorithms, implemented in C language, have an execution time depending on the complexity of the currently processed vascular network.

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Guido Tascini, Giorgio Passerini, Paolo Puliti, and Primo Zingaretti "Robust approach to ocular fundus image analysis", Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); https://doi.org/10.1117/12.148676

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KEYWORDS

Surface conduction electron emitter displays

Detection and tracking algorithms

Edge detection

Blood vessels

Image segmentation

Image analysis

Convolution

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