Digital Image Processing for Ophthalmology: Detection and Modeling of Retinal Vascular Architecture

The monitoring of the effects of retinopathy on the visual system can be assisted by analyzing the vascular architecture of the retina. This book presents methods based on Gabor filters to detect blood vessels in fundus images of the retina. Forty images of the retina from the Digital Retinal Images for Vessel Extraction (DRIVE) database were used to evaluate the performance of the methods. The results demonstrate high efficiency in the detection of blood vessels with an area under the receiver operating characteristic curve of 0.96. Monitoring the openness of the major temporal arcade (MTA) could facilitate improved diagnosis and optimized treatment of retinopathy. This book presents methods for the detection and modeling of the MTA, including the generalized Hough transform to detect parabolic forms. Results obtained with 40 images of the DRIVE database, compared with hand-drawn traces of the MTA, indicate a mean distance to the closest point of about 0.24mm. This book illustrates a plications of the methods mentioned above for the analysis of the effects of proliferative diabetic retinopathy and retinopathy of prematurity on retinal vascular architecture.

[1]  Aliaa A. A. Youssif,et al.  Optic Disc Detection From Normalized Digital Fundus Images by Means of a Vessels' Direction Matched Filter , 2008, IEEE Transactions on Medical Imaging.

[2]  Hans C Fledelius,et al.  Optic disc appearance and retinal temporal vessel arcade geometry in high myopia, as based on follow‐up data over 38 years , 2010, Acta ophthalmologica.

[3]  Rangaraj M. Rangayyan,et al.  Detection of the Optic Nerve Head in Fundus Images of the Retina with Gabor Filters and Phase Portrait Analysis , 2010, Journal of Digital Imaging.

[4]  Anna L. Ells,et al.  The International Classification of Retinopathy of Prematurity revisited. , 2005, Archives of ophthalmology.

[5]  S F Barrett,et al.  Employing the Hough Transform to locate the optic disk. , 2001, Biomedical sciences instrumentation.

[6]  John Flynn,et al.  Characterization of changes in blood vessel width and tortuosity in retinopathy of prematurity using image analysis , 2002, Medical Image Anal..

[7]  A. Ravishankar Rao,et al.  Computing oriented texture fields , 1991, CVGIP Graph. Model. Image Process..

[8]  Juan Xu,et al.  Automated Optic Disk Boundary Detection by Modified Active Contour Model , 2007, IEEE Transactions on Biomedical Engineering.

[9]  Max A. Viergever,et al.  Ridge-based vessel segmentation in color images of the retina , 2004, IEEE Transactions on Medical Imaging.

[10]  A. Bharath,et al.  Computer algorithms for the automated measurement of retinal arteriolar diameters , 2001, The British journal of ophthalmology.

[11]  Michael H. Goldbaum,et al.  Measurement and classification of retinal vascular tortuosity , 1999, Int. J. Medical Informatics.

[12]  J. Daugman.  Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[13]  M. Goldbaum,et al.  Detection of blood vessels in retinal images using two-dimensional matched filters. , 1989, IEEE transactions on medical imaging.

[14]  Pascale Massin,et al.  A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina , 2002, IEEE Transactions on Medical Imaging.

[15]  Scott T. Acton,et al.  A pyramidal algorithm for area morphology , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[16]  Darius M Moshfeghi,et al.  Stanford University Network for Diagnosis of Retinopathy of Prematurity (SUNDROP): Four-years of Screening with Telemedicine , 2013, Current eye research.

[17]  B. S. Manjunath,et al.  Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Xiaohui Zhang,et al.  Detection and classification of bright lesions in color fundus images , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[19]  A. Fulton,et al.  Diagnosis of plus disease in retinopathy of prematurity using Retinal Image multiScale Analysis. , 2005, Investigative ophthalmology & visual science.

[20]  Langis Gagnon,et al.  Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching , 2001, IEEE Transactions on Medical Imaging.

[21]  Huiqi Li,et al.  Automated feature extraction in color retinal images by a model based approach , 2004, IEEE Transactions on Biomedical Engineering.

[22]  R.M. Rangayyan,et al.  Detection of Blood Vessels in the Retina Using Gabor Filters , 2007, 2007 Canadian Conference on Electrical and Computer Engineering.

[23]  Roger Jagoe,et al.  The Measurement of Apparent Vessel Width in Retinal Images - Variation of True Dimensions with Exposure and Development , 1994 .

[24]  Rangaraj M. Rangayyan,et al.  Parabolic Modeling of the Major Temporal Arcade in Retinal Fundus Images , 2012, IEEE Transactions on Instrumentation and Measurement.

[25]  J J Capowski,et al.  Observer sensitivity to retinal vessel diameter and tortuosity in retinopathy of prematurity: a model system. , 1996, Journal of pediatric ophthalmology and strabismus.

[26]  Jeffrey Ng,et al.  Semiautomated digital image analysis of posterior pole vessels in retinopathy of prematurity. , 2009, Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus.

[27]  C. Metz.  Basic principles of ROC analysis. , 1978, Seminars in nuclear medicine.

[28]  Bram van Ginneken,et al.  Information Fusion for Diabetic Retinopathy CAD in Digital Color Fundus Photographs , 2009, IEEE Transactions on Medical Imaging.

[29]  R. Rangayyan,et al.  Detection of Blood Vessels in Fundus Images of the Retina using Gabor Wavelets , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[30]  Anil A. Bharath,et al.  Retinal vascular tree morphology: a semi-automatic quantification , 2002, IEEE Transactions on Biomedical Engineering.

[31]  Michael F Chiang,et al.  Interexpert agreement in the identification of macular location in infants at risk for retinopathy of prematurity. , 2010, Archives of ophthalmology.

[32]  Rangaraj M. Rangayyan,et al.  Detection of the temporal arcade in fundus images of the retina using the hough transform , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[33]  Ching Y. Suen,et al.  Thinning Methodologies - A Comprehensive Survey , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  Andrew Hunter,et al.  Measurement of retinal vessel widths from fundus images based on 2-D modeling , 2004, IEEE Transactions on Medical Imaging.

[35]  Uğur Şevik,et al.  Automatic segmentation of age-related macular degeneration in retinal fundus images , 2008, Comput. Biol. Medicine.

[36]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[37]  E M Kohner,et al.  Does microaneurysm count reflect severity of early diabetic retinopathy? , 1986, Ophthalmology.

[38]  R. T. Smith,et al.  Automated detection of macular drusen using geometric background leveling and threshold selection. , 2005, Archives of ophthalmology.

[39]  T. Fukumura,et al.  An Analysis of Topological Properties of Digitized Binary Pictures Using Local Features , 1975 .

[40]  Tatijana Stosic,et al.  Multifractal analysis of human retinal vessels , 2006, IEEE Transactions on Medical Imaging.

[41]  A.D. Hoover,et al.  Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response , 2000, IEEE Transactions on Medical Imaging.

[42]  Rangaraj M. Rangayyan,et al.  A graphical user interface for measurement of temporal arcade angles in fundus images of the retina , 2012, 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE).

[43]  Azriel Rosenfeld,et al.  Connectivity in Digital Pictures , 1970, JACM.

[44]  H. Fujita,et al.  Detection of retinal nerve fiber layer defects on retinal fundus images for early diagnosis of glaucoma. , 2010, Journal of biomedical optics.

[45]  Mira Park,et al.  Locating the Optic Disc in Retinal Images , 2006, International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06).

[46]  Roberto Marcondes Cesar Junior,et al.  Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification , 2005, IEEE Transactions on Medical Imaging.

[47]  Majid Mirmehdi,et al.  Comparison of colour spaces for optic disc localisation in retinal images , 2002, Object recognition supported by user interaction for service robots.

[48]  Algernon B. Reese,et al.  Ophthalmic Pathology: An Atlas and Textbook , 1953 .

[49]  Rangaraj M. Rangayyan,et al.  Performance Analysis of Oriented Feature Detectors , 2005, XVIII Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI'05).

[50]  Rangaraj M. Rangayyan,et al.  Computer-aided Diagnosis of Proliferative Diabetic Retinopathy via Modeling of the Major Temporal Arcade in Retinal Fundus Images , 2013, Journal of Digital Imaging.

[51]  John G. Daugman,et al.  Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression , 1988, IEEE Trans. Acoust. Speech Signal Process..

[52]  Josef Kittler,et al.  A survey of the hough transform , 1988, Comput. Vis. Graph. Image Process..

[53]  Jyh-Charn S. Liu,et al.  Fractal-based Automatic Localization and Segmentation of Optic Disc in Retinal Images , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[54]  Daniela M. Ushizima,et al.  Vessel network detection using contour evolution and color components , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[55]  Alan Wee-Chung Liew,et al.  General Retinal Vessel Segmentation Using Regularization-Based Multiconcavity Modeling , 2010, IEEE Transactions on Medical Imaging.

[56]  Fahima Nekka,et al.  The Retinal Vasculature: Towards an Understanding of the Formation Process , 1997 .

[57]  Emanuele Trucco,et al.  FABC: Retinal Vessel Segmentation Using AdaBoost , 2010, IEEE Transactions on Information Technology in Biomedicine.

[58]  Rangaraj M. Rangayyan,et al.  Quantitative Analysis of the Major Temporal Arcade in Retinal Fundus Images of Preterm Infants for Detection of Plus Disease , 2013 .

[59]  Charles V. Stewart,et al.  Robust detection and classification of longitudinal changes in color retinal fundus images for monitoring diabetic retinopathy , 2006, IEEE Transactions on Biomedical Engineering.

[60]  K. Parker,et al.  Semiautomated computer analysis of vessel growth in preterm infants without and with ROP , 2003, The British journal of ophthalmology.

[61]  Tien Yin Wong,et al.  ORIGA-light: An online retinal fundus image database for glaucoma analysis and research , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[62]  Rangaraj M. Rangayyan,et al.  Design and performance analysis of oriented feature detectors , 2007, J. Electronic Imaging.

[63]  U. Rajendra Acharya,et al.  Automated Diagnosis of Glaucoma Using Digital Fundus Images , 2009, Journal of Medical Systems.

[64]  Jason Noble,et al.  Diabetic retinopathy , 2010, Canadian Medical Association Journal.

[65]  R C Watzke,et al.  Photographic grading in the retinopathy of prematurity cryotherapy trial. , 1990, Archives of ophthalmology.

[66]  Michael Larsen,et al.  Screening for diabetic retinopathy using a digital non-mydriatic camera compared with standard 35-mm stereo colour transparencies. , 2004, Acta ophthalmologica Scandinavica.

[67]  Bram van Ginneken,et al.  Comparative study of retinal vessel segmentation methods on a new publicly available database , 2004, SPIE Medical Imaging.

[68]  Tony Lindeberg.  Edge Detection and Ridge Detection with Automatic Scale Selection , 2004, International Journal of Computer Vision.

[69]  Alejandro F. Frangi,et al.  Muliscale Vessel Enhancement Filtering , 1998, MICCAI.

[70]  Rangaraj M. Rangayyan,et al.  Methods for the detection of blood vessels in retinal fundus images and reduction of false-positive pixels around the optic nerve head , 2013, 2013 E-Health and Bioengineering Conference (EHB).

[71]  Mong-Li Lee,et al.  An effective approach to detect lesions in color retinal images , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[72]  Rangaraj M. Rangayyan,et al.  Dual-parabolic modeling of the superior and the inferior temporal arcades in fundus images of the retina , 2011, 2011 IEEE International Symposium on Medical Measurements and Applications.

[73]  Penny Jennett,et al.  Telemedicine approach to screening for severe retinopathy of prematurity: a pilot study. , 2003, Ophthalmology.

[74]  Frédéric Zana,et al.  Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation , 2001, IEEE Trans. Image Process..

[75]  Rangaraj M. Rangayyan,et al.  Landmarking and Segmentation of 3D CT Images , 2009, Landmarking and Segmentation of 3D CT Images.

[76]  Gwénolé Quellec,et al.  Optimal Wavelet Transform for the Detection of Microaneurysms in Retina Photographs , 2008, IEEE Transactions on Medical Imaging.

[77]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[78]  Mohammed Al-Rawi,et al.  An improved matched filter for blood vessel detection of digital retinal images , 2007, Comput. Biol. Medicine.

[79]  Peter Wiedemann,et al.  Vitrectomy for traction macular detachment in diabetic retinopathy , 1997, Graefe's Archive for Clinical and Experimental Ophthalmology.

[80]  D. Wallace,et al.  Prognostic significance of vascular dilation and tortuosity insufficient for plus disease in retinopathy of prematurity. , 2000, Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus.

[81]  Jeffrey E. Boyd,et al.  Automated diagnosis and image understanding with object extraction, object classification, and inferencing in retinal images , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[82]  S. T. Clay,et al.  Optic disk size and optic disk-to-fovea distance in preterm and full-term infants. , 2006, Investigative ophthalmology & visual science.

[83]  Giri Babu Kande,et al.  Automatic Detection of Microaneurysms and Hemorrhages in Digital Fundus Images , 2010, Journal of Digital Imaging.

[84]  Anna L Ells,et al.  Retinopathy of prematurity--the movie. , 2004, Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus.

[85]  Xiaoyi Jiang,et al.  Adaptive Local Thresholding by Verification-Based Multithreshold Probing with Application to Vessel Detection in Retinal Images , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[86]  Rangaraj M. Rangayyan,et al.  Detection of blood vessels in the retina with multiscale Gabor filters , 2008, J. Electronic Imaging.

[87]  J. P. Jones,et al.  An evaluation of the two-dimensional Gabor filter model of simple receptive fields in cat striate cortex. , 1987, Journal of neurophysiology.

[88]  Ming Zhang,et al.  On the Small Vessel Detection in High Resolution Retinal Images , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[89]  Shankar M. Krishnan,et al.  Detection and measurement of retinal vessels in fundus images using amplitude modified second-order Gaussian filter , 2002, IEEE Transactions on Biomedical Engineering.

[90]  C. Sinthanayothin,et al.  Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images , 1999, The British journal of ophthalmology.

[91]  Rangaraj M. Rangayyan,et al.  Directional image analysis with the Hough and Radon transforms , 2013 .

[92]  Harry Wechsler,et al.  Finding the rib cage in chest radiographs , 1977, Pattern Recognit..

[93]  Hermawan Nugroho,et al.  Analysis of foveal avascular zone in colour fundus images for grading of diabetic retinopathy severity , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[94]  Ronald Klein,et al.  The comparability of estimates of retroilluminated lens opacities as judged from film-based and digital imaging. , 2004, American journal of ophthalmology.

[95]  R. Klein,et al.  Retinal microaneurysm counts and 10-year progression of diabetic retinopathy. , 1995, Archives of ophthalmology.

[96]  Kenneth W. Tobin,et al.  Detection of Anatomic Structures in Human Retinal Imagery , 2007, IEEE Transactions on Medical Imaging.

[97]  Karl-Hans Englmeier,et al.  Course tracking and contour extraction of retinal vessels from color fundus photographs: most efficient use of steerable filters for model-based image analysis , 1998, Medical Imaging.

[98]  Enrico Grisan,et al.  Detection of optic disc in retinal images by means of a geometrical model of vessel structure , 2004, IEEE Transactions on Medical Imaging.

[99]  P. Gregson,et al.  Automated grading of venous beading. , 1995, Computers and biomedical research, an international journal.

[100]  José Manuel Bravo,et al.  A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features , 2011, IEEE Transactions on Medical Imaging.

[101]  Emanuele Trucco,et al.  A Comparative Study on Feature Selection for Retinal Vessel Segmentation Using FABC , 2009, CAIP.

[102]  David Zhang,et al.  A Modified Matched Filter With Double-Sided Thresholding for Screening Proliferative Diabetic Retinopathy , 2009, IEEE Transactions on Information Technology in Biomedicine.

[103]  Jack Sklansky,et al.  On the Hough Technique for Curve Detection , 1978, IEEE Transactions on Computers.

[104]  Jyh-Charn Liu,et al.  Automated localization of macula-fovea area on retina images using blood vessel network topology , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[105]  Gabriella Sanniti di Baja,et al.  Skeletons of planar patterns , 1996 .

[106]  Usha Chakravarthy,et al.  Grading of age-related maculopathy for epidemiological studies: is digital imaging as good as 35-mm film? , 2003, Ophthalmology.

[107]  Jeffrey Ng,et al.  The temporal and nasal retinal arteriolar and venular angles in preterm infants , 2011, British Journal of Ophthalmology.

[108]  Michael H. Goldbaum,et al.  Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels , 2003, IEEE Transactions on Medical Imaging.

[109]  Tien Yin Wong,et al.  Retinal arteriolar narrowing, hypertension, and subsequent risk of diabetes mellitus. , 2005, Archives of internal medicine.

[110]  A R Fielder,et al.  The temporal retinal vessel angle and infants born preterm , 2006, British Journal of Ophthalmology.

[111]  Jing Li Wang,et al.  Color image segmentation: advances and prospects , 2001, Pattern Recognit..

[112]  Michael F Chiang,et al.  Agreement among pediatric ophthalmologists in diagnosing plus and pre-plus disease in retinopathy of prematurity. , 2008, Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus.

[113]  Azriel Rosenfeld,et al.  Digital topology: Introduction and survey , 1989, Comput. Vis. Graph. Image Process..

[114]  Andrew Hunter,et al.  An Active Contour Model for Segmenting and Measuring Retinal Vessels , 2009, IEEE Transactions on Medical Imaging.

[115]  Kwang Suk Park,et al.  Segmentation of sperms using the strategic hough transform , 1997, Annals of Biomedical Engineering.

[116]  Lew Fock Chong Lew Yan Voon,et al.  Detecting parabolas in ultrasound B-scan images with Genetic-Based Inverse Voting Hough Transform , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[117]  Rangaraj M. Rangayyan,et al.  Feature identification in the time-frequency plane by using the Hough-Radon transform , 2001, Pattern Recognit..

[118]  Rangaraj M. Rangayyan,et al.  Parametric representation of the retinal temporal arcade , 2010, Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine.

[119]  I. Deary,et al.  Retinal image analysis: Concepts, applications and potential , 2006, Progress in Retinal and Eye Research.

[120]  Josef Kittler,et al.  A formal definition of the Hough transform: Properties and relationships , 2004, Journal of Mathematical Imaging and Vision.

[121]  R. Klein,et al.  Abnormalities of Retinal Microvascular Structure and Risk of Mortality From Ischemic Heart Disease and Stroke , 2006, Hypertension.

[122]  Farzin Deravi,et al.  Efficient algorithm for the detection of parabolic curves , 1995, Other Conferences.

[123]  Charles V. Stewart,et al.  Retinal Vessel Centerline Extraction Using Multiscale Matched Filters, Confidence and Edge Measures , 2006, IEEE Transactions on Medical Imaging.

[124]  Rangaraj M. Rangayyan,et al.  Detection of the Optic Nerve Head in Fundus Images of the Retina Using the Hough Transform for Circles , 2010, Journal of Digital Imaging.

[125]  S. T. Clay,et al.  Computerized analysis of retinal vessel width and tortuosity in premature infants. , 2008, Investigative ophthalmology & visual science.