M. Elena Martínez-Pérez

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The morphology of the retinal blood vessels can be an important indicator for diseases like diabetes, hypertension and retinopathy of prematurity (ROP). Thus, the measurement of changes in morphology of arterioles and venules can be of diagnostic value. Here we present a method to automatically segment retinal blood vessels based upon multiscale feature(More)
A semi-automatic method to measure and quantify geometrical and topological properties of continuous vascular trees in clinical fundus images is described. Measurements are made from binary images obtained with a previously described segmentation process. The skeletons of the segmented trees are produced by thinning,ff branch and crossing points are(More)
This paper presents a parallel implementation based on insight segmentation and registration toolkit for a multiscale feature extraction and region growing algorithm, applied to retinal blood vessels segmentation. This implementation is capable of achieving an accuracy (Ac) comparable to its serial counterpart (about 92%), but 8 to 10 times faster. In this(More)
In this paper, we propose a highly robust point-matching method (Graph Transformation Matching-GTM) relying on finding the consensus graph emerging from putative matches. Such method is a two-phased one in the sense that after finding the consensus graph it tries to complete it as much as possible. We successfully apply GTM to image registration in the(More)
Various methods for detecting optic disc and macula in fundus images have been developed. Our aim is to propose a fairly easy method for detecting both features jointly. This is achieved by first correcting in homogenous luminosity using a polynomial approximation of the background of the images. Secondly, the use of the cross-correlation in the frequency(More)