title: A novel method for retinal vessel tracking using particle filters.
abstract: Extraction of a proper map from the vessel paths in the retinal images is a prerequisite for many applications such as identification. In this paper, we present a new approach based on particle filtering to determine and locally track the vessel paths in retina. Particle filter needs to use an acceptable probability density function (PDF) describing the blood vessels which must be provided by the retinal image. For this purpose, the product of the green and blue channels of the RGB retinal images is considered and after a median filtering stage, it is used as a PDF for tracking procedure. Then a stage of optic disc localization is performed to localize the starting points around the optic disc. With a proper set of starting points, the iterative tracking procedure initiates. First, a uniform propagation of the particles on an annular ring around each point (including starting points or ones determined as central points in the previous iteration) is performed. The particle weights are evaluated and accordingly, each particle is decided to be inside or outside the vessel. The subsequent stage is to analyze the hypothetical vectors between a central point and each of the inside vessel particles to find ones located inside vessel. Afterwards, the particles are clustered using quality threshold clustering method. Finally, each cluster introduces a central point for pursuing the tracking procedure in the next iteration. The tracking proceeds towards a bifurcation or the end of the vessels. We introduced two criteria: automatic/manually tracked ratio (AMTR) and false/manually tracked ratio (FMTR) for evaluating the tracking results. Apart from the labeling accuracy, the average values of AMTR and FMTR were 0.7746 and 0.2091, respectively. The proposed method successfully deals with the bifurcations with robustness against noise and tracks the thin vessels.
authors: Department of Electrical Engineering, K.N. Toosi University of Technology, Seyed Khandan, P.O. Box 16315-1355, Tehran, Iran. Bahador.Nayebifar@ieee.org
authors: B
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authors: Nayebifar
authors: H
authors: H
authors: Abrishami Moghaddam
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D003941:Diagnostic Techniques, Ophthalmological; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009010:Monte Carlo Method; D012160:Retina / Q000033:anatomy & histology*; D012171:Retinal Vessels / Q000033:anatomy & histology*