2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) 2016
DOI: 10.1109/isbi.2016.7493241
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Automatic detection of vascular bifurcations and crossings in retinal images using orientation scores

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Cited by 34 publications
(42 citation statements)
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“…Moreover, we use the IOSTAR dataset [6,20] for testing the robustness of the method. Our networks are trained on the DRIVE Dataset, but all of them are tested on the unseen IOSTAR dataset for further validation.…”
Section: Datasetsmentioning
confidence: 99%
See 2 more Smart Citations
“…Moreover, we use the IOSTAR dataset [6,20] for testing the robustness of the method. Our networks are trained on the DRIVE Dataset, but all of them are tested on the unseen IOSTAR dataset for further validation.…”
Section: Datasetsmentioning
confidence: 99%
“…The previous work on vessel bifurcations and junctions has involved using orientation scores to detect bifurcations and junctions in retinal images [6]. In contrast to the method we proposed, which is a fully automated system that uses only the image to determine the diagnosis, the work in [6] required 24 orientation processes for each image before training.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Not only the vessel properties at these points provides relevant clinical information [11], but also they are considered as key points in vessel tracking methods, which represent the graphical model of the vasculature. For the vessel junction detection, we have used the BICROS method described in [1]. In this method, after applying appropriate preprocessing, the image is lifted with anisotropic (single-sided) cake wavelets with 24 orientations as described in Sec.…”
Section: Bifurcations and Crossing Detectionmentioning
confidence: 99%
“…1(i)). The method has been validated quantitatively and qualitatively using two public datasets [1].…”
Section: Bifurcations and Crossing Detectionmentioning
confidence: 99%