Int J Comput Assist Radiol Surg - Delineation of blood vessels in pediatric retinal images using decision trees-based ensemble classification.

Tópicos

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Resumo

RPOSE: Automatic segmentation of the retinal vasculature is a first step in computer-assisted diagnosis and treatment planning. The extraction of retinal vessels in pediatric retinal images is challenging because of comparatively wide arterioles with a light streak running longitudinally along the vessel's center, the central vessel reflex. A new method for automatic segmentation was developed and tested.METHOD: A supervised method for retinal vessel segmentation in the images of multi-ethnic school children was developed based on ensemble classifier of bootstrapped decision trees. A collection of dual Gaussian, second derivative of Gaussian and Gabor filters, along with the generalized multiscale line strength measure and morphological transformation is used to generate the feature vector. The feature vector encodes information to handle the normal vessels as well as the vessels with the central reflex. The methodology is evaluated on CHASE_DB1, a relatively new public retinal image database of multi-ethnic school children, which is a subset of retinal images from the Child Heart and Health Study in England (CHASE) dataset.RESULTS: The segmented retinal images from the CHASE_DB1 database produced best case accuracy, sensitivity and specificity of 0.96, 0.74 and 0.98, respectively, and worst case measures of 0.94, 0.67 and 0.98, respectively.CONCLUSION: A new retinal blood vessel segmentation algorithm was developed and tested with a shared database. The observed accuracy, speed, robustness and simplicity suggest that the algorithm may be a suitable tool for automated retinal image analysis in large population-based studies.

Resumo Limpo

rpose automat segment retin vasculatur first step computerassist diagnosi treatment plan extract retin vessel pediatr retin imag challeng compar wide arteriol light streak run longitudin along vessel center central vessel reflex new method automat segment develop testedmethod supervis method retin vessel segment imag multiethn school children develop base ensembl classifi bootstrap decis tree collect dual gaussian second deriv gaussian gabor filter along general multiscal line strength measur morpholog transform use generat featur vector featur vector encod inform handl normal vessel well vessel central reflex methodolog evalu chasedb relat new public retin imag databas multiethn school children subset retin imag child heart health studi england chase datasetresult segment retin imag chasedb databas produc best case accuraci sensit specif respect worst case measur respectivelyconclus new retin blood vessel segment algorithm develop test share databas observ accuraci speed robust simplic suggest algorithm may suitabl tool autom retin imag analysi larg populationbas studi

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