A high performance hardware architecture for portable, low-power retinal vessel segmentation
- 1 June 2014
- journal article
- Published by Elsevier BV in Integration
- Vol. 47 (3), 377-386
- https://doi.org/10.1016/j.vlsi.2013.11.005
Abstract
No abstract availableFunding Information
- European Regional Development Fund and the Republic of Cyprus through the Research Promotion Foundation (ΥΠΟΔΟΜΗ/ΣΤΡΑΤΗ/0308/26, ΠΕΝΕΚ/0311/32)
This publication has 20 references indexed in Scilit:
- Automatic vessel network features quantification using local vessel pattern operatorComputers in Biology and Medicine, 2013
- Hardware acceleration of retinal blood vasculature segmentationPublished by Association for Computing Machinery (ACM) ,2013
- Blood vessel segmentation methodologies in retinal images – A surveyComputer Methods and Programs in Biomedicine, 2012
- Digital Ocular Fundus Imaging: A ReviewOphthalmologica, 2011
- A robust person authentication system based on score level fusion of left and right irises and retinal featuresProcedia Computer Science, 2010
- FPGA-accelerated retinal vessel-tree extractionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- Pixel parallel vessel tree extraction for a personal authentication systemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2008
- Cellular Neural Networks With Virtual Template Expansion for Retinal Vessel SegmentationIEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 2007
- Characterization of changes in blood vessel width and tortuosity in retinopathy of prematurity using image analysisMedical Image Analysis, 2002
- Locating blood vessels in retinal images by piecewise threshold probing of a matched filter responseIEEE Transactions on Medical Imaging, 2000