Characterization of changes in blood vessel width and tortuosity in retinopathy of prematurity using image analysis

By Conor Heneghan, J. Flynn, M. O'Keefe, M. Cahill. Medical Image Anal., 2002

373 citations recorded by the source corpus.

Subfields: Pediatrics, Perinatology and Child Health, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/d72589fa56aa0cc3a9855a7c29c082261518d46d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Pediatrics, Perinatology and Child Health

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features (2011, methodology): “Other methods use mathematical morphology [15], [34]–[36] to benefit from a priori-known vasculature shape features, such as being piecewise linear and connected.”
Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement (2012, methodology): “Also, by making measurements directly from the segmented images, the final results may be unduly influenced by thresholds used in the binarisation stages [27].”
Luminosity and contrast normalization in retinal images (2005, background): “Retinal lesions, related both to vascular aspects, such as increased vessel tortuosity (Hart et al., 1999; Heneghan et al., 2002) or focal/generalized narrowing (Hubbard et al., 1999), and to non-vascular features, such as haemorrhages, exudates, microaneurysms and others (Ege et al., 2000), are…”
Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction (2006, background): “Some of the main clinical objectives reported in the literature for retinal vessel segmentation are the implementation of screening programs for diabetic retinopathy [3]–[5], evaluation of the retinopathy of prematurity [6], macular avascular region detection [7], arteriolar narrowing [8], [9], vess”
Retinal image analysis: concepts, applications and potential. (2006, background): “In 1995, Capowski et al. (1995) reported using an arterial tortuosity index from fundal photographs as a useful measure of ROP disease state.”
Detecting the Optic Disc Boundary in Digital Fundus Images Using Morphological, Edge Detection, and Feature Extraction Techniques (2010, background): “in [27], the value for this parameter was set to 27.”
An approach to localize the retinal blood vessels using bit planes and centerline detection (2012, background): “E-mail address: moazam fraz@yahoo.com (M.M. Fraz). of screening programs for diabetic retinopathy [3], the evaluation of retinopathy of prematurity [4], foveal avascular region detection [5], arteriolar narrowing detection [6], the determination of the relationship between vessel tortuosity and…”
Trainable COSFIRE filters for vessel delineation with application to retinal images (2015, methodology): “Other unsupervised methods, which use a priori information about the profile structure of the vessels, employ mathematical morphology to segment the vessel tree from the background (Zana and Klein, 2001; Heneghan et al., 2002; Mendonca and Campilho, 2006).”
Retinal Vessel Centerline Extraction Using Multiscale Matched Filters, Confidence and Edge Measures (2006, methodology): “The techniques published in the research literature in response to the importance of retinal vessel extraction may be roughly categorized into methods based on matched filters [24], [30], [31], adaptive thresholds [31], [32], intensity edges [33], [34], region growing [35], statistical inferencing [”