PURPOSE: To determine, with novel software, the feasibility of measuring the tortuosity and width of retinal veins and arteries from digital retinal images of infants at risk of retinopathy of prematurity (ROP). METHODS: The Computer-Aided Image Analysis of the Retina (CAIAR) program was developed to enable semiautomatic detection of retinal vasculature and measurement of vessel tortuosity and width from digital images. CAIAR was tested for accuracy and reproducibility of tortuosity and width measurements by using computer-generated vessel-like lines of known frequency, amplitude, and width. CAIAR was then tested by using clinical digital retinal images for correlation of vessel tortuosity and width readings compared with expert ophthalmologist grading. RESULTS: When applied to 16 computer-generated sinusoidal vessels, the tortuosity measured by CAIAR correlated very well with the known values. Width measures also increased as expected. When the CAIAR readings were compared with five expert ophthalmologists' grading of 75 vessels on 10 retinal images, moderate correlation was found in 10 of the 14 tortuosity output calculations (Spearman rho = 0.618-0.673). Width was less well correlated (rho = 0.415). CONCLUSIONS: The measures of tortuosity and width in CAIAR were validated using sequential model vessel analysis. On comparison of CAIAR output with assessments made by expert ophthalmologists, CAIAR correlates moderately with tortuosity grades, but less well with width grades. CAIAR offers the opportunity to develop an automated image analysis system for detecting the vascular changes at the posterior pole, which are becoming increasingly important in diagnosing treatable ROP.
PURPOSE: To determine, with novel software, the feasibility of measuring the tortuosity and width of retinal veins and arteries from digital retinal images of infants at risk of retinopathy of prematurity (ROP). METHODS: The Computer-Aided Image Analysis of the Retina (CAIAR) program was developed to enable semiautomatic detection of retinal vasculature and measurement of vessel tortuosity and width from digital images. CAIAR was tested for accuracy and reproducibility of tortuosity and width measurements by using computer-generated vessel-like lines of known frequency, amplitude, and width. CAIAR was then tested by using clinical digital retinal images for correlation of vessel tortuosity and width readings compared with expert ophthalmologist grading. RESULTS: When applied to 16 computer-generated sinusoidal vessels, the tortuosity measured by CAIAR correlated very well with the known values. Width measures also increased as expected. When the CAIAR readings were compared with five expert ophthalmologists' grading of 75 vessels on 10 retinal images, moderate correlation was found in 10 of the 14 tortuosity output calculations (Spearman rho = 0.618-0.673). Width was less well correlated (rho = 0.415). CONCLUSIONS: The measures of tortuosity and width in CAIAR were validated using sequential model vessel analysis. On comparison of CAIAR output with assessments made by expert ophthalmologists, CAIAR correlates moderately with tortuosity grades, but less well with width grades. CAIAR offers the opportunity to develop an automated image analysis system for detecting the vascular changes at the posterior pole, which are becoming increasingly important in diagnosing treatable ROP.
Authors: Preeti J Thyparampil; Yangseon Park; M E Martinez-Perez; Thomas C Lee; David J Weissgold; Audina M Berrocal; R V Paul Chan; John T Flynn; Michael F Chiang Journal: Am J Ophthalmol Date: 2010-10 Impact factor: 5.258
Authors: Emanuele Trucco; Alfredo Ruggeri; Thomas Karnowski; Luca Giancardo; Edward Chaum; Jean Pierre Hubschman; Bashir Al-Diri; Carol Y Cheung; Damon Wong; Michael Abràmoff; Gilbert Lim; Dinesh Kumar; Philippe Burlina; Neil M Bressler; Herbert F Jelinek; Fabrice Meriaudeau; Gwénolé Quellec; Tom Macgillivray; Bal Dhillon Journal: Invest Ophthalmol Vis Sci Date: 2013-05-01 Impact factor: 4.799
Authors: Rohini Rao; Nina J Jonsson; Camila Ventura; Rony Gelman; Martin A Lindquist; Daniel S Casper; Michael F Chiang Journal: Retina Date: 2012-06 Impact factor: 4.256