International Journal of Reviews in Computing an Overview of Computational Intelligence Techniques for Retinal Disease Identification Applications (review Paper)

Computational methodologies have become a significant part of the real time applications. One specific application which highly depends on the computing techniques is the medical field. Ophthalmology is a significant branch of biomedical field which requires computer-aided automated techniques for pathology identification in human eyes. These automated techniques must be highly accurate and also converge in quick time period. Based on these criterions, several automated techniques are developed and being used for practical applications. Even though many techniques are available, it is very difficult to achieve the concept of generalization among these automated techniques. Hence, there is a significant necessity for analyzing the various techniques in order to highlight their suitability for eye disease identification applications. This research paper overcomes this deficiency by providing an in-depth analysis of the existing automated techniques. The focus of this paper is on Artificial Intelligence (AI) based techniques since these techniques are found to be superior to other computing techniques. An extensive analysis is performed to bring out the merits and demerits of various Artificial Intelligence (AI) based techniques. Thus the application of AI techniques for retinal disease identification is explored in this work. This work also indirectly suggests AI based solutions for the various stages of automated retinal disease diagnosis system.

[1]  Peter Tino,et al.  IEEE Transactions on Neural Networks , 2009 .

[2]  Anil A. Bharath,et al.  Segmentation of blood vessels from red-free and fluorescein retinal images , 2007, Medical Image Anal..

[3]  Frans Vos,et al.  A model based method for retinal blood vessel detection , 2004, Comput. Biol. Medicine.

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

[5]  Frédéric Zana,et al.  A multimodal registration algorithm of eye fundus images using vessels detection and Hough transform , 1999, IEEE Transactions on Medical Imaging.

[6]  Sameh A. Salem,et al.  Segmentation of retinal blood vessels based on analysis of the hessian matrix and Clustering Algorithm , 2007, 2007 15th European Signal Processing Conference.

[7]  Ana Maria Mendonça,et al.  Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction , 2006, IEEE Transactions on Medical Imaging.

[8]  Hiroshi Ishikawa,et al.  Macular segmentation with optical coherence tomography. , 2005, Investigative ophthalmology & visual science.

[9]  Heinrich Niemann,et al.  Automated segmentation of the optic nerve head for diagnosis of glaucoma , 2005, Medical Image Anal..

[10]  Frans Vos,et al.  Modeling of scanning laser polarimetry images of the human retina for progression detection of glaucoma , 2006, IEEE Transactions on Medical Imaging.

[11]  Mohammed Al-Rawi,et al.  Genetic algorithm matched filter optimization for automated detection of blood vessels from digital retinal images , 2007, Comput. Methods Programs Biomed..

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

[13]  P Agostino Accardo,et al.  Neural network-based system for early keratoconus detection from corneal topography , 2002, J. Biomed. Informatics.

[14]  Juan Xu,et al.  Optic disk feature extraction via modified deformable model technique for glaucoma analysis , 2007, Pattern Recognit..

[15]  Daniele D. Giusto,et al.  Retinal Image Segmentation by Watersheds , 2000, MVA.

[16]  Roberto Marcondes Cesar Junior,et al.  Blood vessels segmentation in retina: preliminary assessment of the mathematical morphology and of the wavelet transform techniques , 2001, Proceedings XIV Brazilian Symposium on Computer Graphics and Image Processing.

[17]  Kotagiri Ramamohanarao,et al.  Blood Vessel Segmentation from Color Retinal Images using Unsupervised Texture Classification , 2007, 2007 IEEE International Conference on Image Processing.

[18]  Yong Yang,et al.  An Automatic Hybrid Method for Retinal Blood Vessel Extraction , 2008, Int. J. Appl. Math. Comput. Sci..

[19]  J. Suri,et al.  Automatic identification of anterior segment eye abnormality , 2007 .

[20]  Bunyarit Uyyanonvara,et al.  Automatic Exudate Detection from Non-dilated Diabetic Retinopathy Retinal Images Using Fuzzy C-means Clustering , 2009, Sensors.

[21]  Giri Babu Kande,et al.  Segmentation of Vessels in Fundus Images using Spatially Weighted Fuzzy c-Means Clustering Algorithm , 2007 .

[22]  Philip J. Morrow,et al.  Algorithms for digital image processing in diabetic retinopathy , 2009, Comput. Medical Imaging Graph..

[23]  A. Salvatelli,et al.  A comparative analysis of pre-processing techniques in colour retinal images , 2007 .

[24]  Amrita Roy Chowdhury,et al.  Automatic Drusen Detection and Area Calculation from Color Retinal Images , 2012 .

[25]  Majid Mirmehdi,et al.  Comparative Exudate Classification Using Support Vector Machines and Neural Networks , 2002, MICCAI.

[26]  Gady Agam,et al.  A general framework for vessel segmentation in retinal images , 2007, 2007 International Symposium on Computational Intelligence in Robotics and Automation.

[27]  Paul L. Rosin,et al.  Multimodal retinal imaging: new strategies for the detection of glaucoma , 2002, Proceedings. International Conference on Image Processing.

[28]  U. Rajendra Acharya,et al.  Automated Identification of Diabetic Retinopathy Stages Using Digital Fundus Images , 2008, Journal of Medical Systems.

[29]  Kamel Hamrouni,et al.  Detection of Blood Vessels in Retinal Images , 2010, Int. J. Image Graph..

[30]  Elisa Ricci,et al.  Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification , 2007, IEEE Transactions on Medical Imaging.

[31]  Asoke K. Nandi,et al.  Automated localisation of optic disk and fovea in retinal fundus images , 2008, 2008 16th European Signal Processing Conference.

[32]  Povilas Treigys.  NEURAL NETWORK AS AN OPHTHALMOLOGIC DISEASE CLASSIFIER , 2007 .

[33]  S. S. Shylaja,et al.  Algorithmic Approach for Prediction and Early Detection of Diseases Using Retinal Images , 2007, Computer Graphics, Imaging and Visualisation (CGIV 2007).

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

[35]  Andrew Hunter,et al.  Lesion Boundary Segmentation using Level Set Methods , 2009, VISAPP.

[36]  Lei Zhang,et al.  Retinal vessel extraction by matched filter with first-order derivative of Gaussian , 2010, Comput. Biol. Medicine.

[37]  Kim L. Boyer,et al.  Automatic recovery of the optic nervehead geometry in optical coherence tomography , 2006, IEEE Transactions on Medical Imaging.

[38]  Andrew Hunter,et al.  Optic nerve head segmentation , 2004, IEEE Transactions on Medical Imaging.

[39]  Guoliang Fan,et al.  Retinal Spot Lesion Detection Using Adaptive Multiscale Morphological Processing , 2006, ISVC.

[40]  D. Jayanthi,et al.  Automatic diagnosis of retinal diseases from color retinal images , 2010, ArXiv.

[41]  Young H. Kwon,et al.  Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features. , 2007, Investigative ophthalmology & visual science.

[42]  Federico Bizzarri,et al.  A modular supervised algorithm for vessel segmentation in red-free retinal images , 2008, Comput. Biol. Medicine.

[43]  Lalit M. Patnaik,et al.  Application of genetic programming for multicategory pattern classification , 2000, IEEE Trans. Evol. Comput..

[44]  Musbah M. Aqel,et al.  Pattern recognition using multilayer neural-genetic algorithm , 2003, Neurocomputing.

[45]  Jayanthi Sivaswamy,et al.  Unsupervised curvature-based retinal vessel segmentation , 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[46]  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.

[47]  Jaspreet Kaur,et al.  An Efficient Blood Vessel Detection Algorithm For Retinal Images Using Local Entropy Thresholding , 2012 .

[48]  P. Mitchell,et al.  Development of retinal blood vessel segmentation methodology using wavelet transforms for assessment of diabetic retinopathy , 2009 .

[49]  B. van Ginneken,et al.  Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis. , 2007, Investigative ophthalmology & visual science.

[50]  Philip J. Morrow,et al.  Optic Nerve Head Segmentation in HRT Images , 2006, 2006 International Conference on Image Processing.

[51]  Tao Zhu,et al.  Fourier cross-sectional profile for vessel detection on retinal images , 2010, Comput. Medical Imaging Graph..

[52]  Herbert F. Jelinek,et al.  Vessel segmentation and tracking using a two-dimensional model , 2005 .

[53]  Nikhil R. Pal,et al.  A neuro-fuzzy scheme for simultaneous feature selection and fuzzy rule-based classification , 2004, IEEE Transactions on Neural Networks.

[54]  Dogan Aydin,et al.  Detection of blood vessels in ophthalmoscope images using MF/ant (matched filter/ant colony) algorithm , 2009, Comput. Methods Programs Biomed..

[55]  Magnus Borga,et al.  Blood vessel segmentation using multi-scale quadrature filtering , 2010, Pattern Recognit. Lett..

[56]  Cemal Köse,et al.  A Statistical Segmentation Method for Measuring Age-Related Macular Degeneration in Retinal Fundus Images , 2010, Journal of Medical Systems.

[57]  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.

[58]  Aliaa A. A. Youssif,et al.  Comparative Study of Contrast Enhancement and Illumination Equalization Methods for Retinal Vasculat , 2006 .

[59]  Gady Agam,et al.  Probabilistic retinal vessel segmentation , 2007, SPIE Medical Imaging.

[60]  Gerald Schaefer,et al.  Segmentation of optic disc in retinal images using an improved gradient vector flow algorithm , 2009, Multimedia Tools and Applications.

[61]  Roberto M. Cesar,et al.  Retinal Vasculature Segmentation Using Wavelets and Supervised Classification , 2007 .

[62]  Ahmed Wasif Reza,et al.  Diagnosis of Diabetic Retinopathy: Automatic Extraction of Optic Disc and Exudates from Retinal Images using Marker-controlled Watershed Transformation , 2009, Journal of Medical Systems.

[63]  Yasser M. Kadah,et al.  Survey of Retinal Image Segmentation and Registration , 2006 .

[64]  Andrew Hunter,et al.  Tram-Line filtering for retinal vessel segmentation , 2005 .

[65]  Wei Jin,et al.  Enhancing retinal image by the Contourlet transform , 2007, Pattern Recognit. Lett..

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

[67]  Langis Gagnon,et al.  Procedure to detect anatomical structures in optical fundus images , 2001, SPIE Medical Imaging.

[68]  Hong Yan,et al.  A Novel Vessel Segmentation Algorithm for Pathological Retina Images Based on the Divergence of Vector Fields , 2008, IEEE Transactions on Medical Imaging.

[69]  Marios S. Pattichis,et al.  Multiscale AM-FM Methods for Diabetic Retinopathy Lesion Detection , 2010, IEEE Transactions on Medical Imaging.

[70]  J Bigun,et al.  Model based segmentation for retinal fundus images , 2003 .

[71]  Bram van Ginneken,et al.  Fast detection of the optic disc and fovea in color fundus photographs , 2009, Medical Image Anal..

[72]  Evangelos Dermatas,et al.  Multi-scale retinal vessel segmentation using line tracking , 2010, Comput. Medical Imaging Graph..

[73]  Roberto Marcondes Cesar Junior,et al.  Retinal Vessel Segmentation Using the 2-D Morlet Wavelet and Supervised Classification , 2005, ArXiv.

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

[75]  Bram van Ginneken,et al.  Segmentation of the Optic Disc, Macula and Vascular Arch in Fundus Photographs , 2007, IEEE Transactions on Medical Imaging.

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

[77]  Enrico Grisan,et al.  Luminosity and contrast normalization in retinal images , 2005, Medical Image Anal..

[78]  Mariano Rincón,et al.  Identification of the optic nerve head with genetic algorithms , 2008, Artif. Intell. Medicine.

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

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

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

[82]  Til Aach,et al.  Supervised, hysteresis-based segmentation of retinal images using the linear-classifier percentile , 2009, GI Jahrestagung.

[83]  Jie Tian,et al.  Retinal vessel enhancement based on directional field , 2008, SPIE Medical Imaging.

[84]  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.

[85]  Bashir Al-Diri,et al.  Automated analysis of retinal vascular network connectivity , 2010, Comput. Medical Imaging Graph..

[86]  Xiaodong Wu,et al.  Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search , 2008, IEEE Transactions on Medical Imaging.

[87]  Lei Zhang,et al.  Automated Retinal Vessel Segmentation Using Multiscale Analysis and Adaptive Thresholding , 2006, 2006 IEEE Southwest Symposium on Image Analysis and Interpretation.

[88]  Manuel G. Penedo,et al.  Retinal vessel tree segmentation using a deformable contour model , 2008, 2008 19th International Conference on Pattern Recognition.

[89]  Sameh A. Salem,et al.  Segmentation of retinal blood vessels using a novel clustering algorithm (RACAL) with a partial supervision strategy , 2007, 2006 14th European Signal Processing Conference.

[90]  Asoke K. Nandi,et al.  Novel and adaptive contribution of the red channel in pre-processing of colour fundus images , 2007, J. Frankl. Inst..

[91]  O. Chutatape,et al.  Retinal blood vessel detection and tracking by matched Gaussian and Kalman filters , 1998, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286).

[92]  Manuel G. Penedo,et al.  Localisation of the optic disc by means of GA-optimised Topological Active Nets , 2009, Image Vis. Comput..

[93]  Jayanthi Sivaswamy,et al.  Colour Retinal Image Enhancement Based on Domain Knowledge , 2008, 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing.

[94]  April Khademi,et al.  Shift-invariant discrete wavelet transform analysis for retinal image classification , 2007, Medical & Biological Engineering & Computing.

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

[96]  Marco Russo,et al.  Genetic fuzzy learning , 2000, IEEE Trans. Evol. Comput..

[97]  Roberto Hornero,et al.  A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis. , 2008, Medical engineering & physics.

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

[99]  S. Balasubramanian,et al.  Automatic Detection of Anatomical Structures in Digital Fundus Retinal Images , 2007, MVA.

[100]  Simon P. Harding,et al.  Enhancement of blood vessels in digital fundus photographs via the application of multiscale line operators , 2008, J. Frankl. Inst..

[101]  U. Rajendra Acharya,et al.  Application of Higher Order Spectra for the Identification of Diabetes Retinopathy Stages , 2008, Journal of Medical Systems.

[102]  Hee Chan Kim,et al.  Segmentation of Optic Nerve Head using Warping and RANSAC , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[103]  B. Uyyanonvara,et al.  AUTOMATIC OPTIC DISK DETECTION FROM LOW CONTRAST RETINAL IMAGES OF ROP INFANT USING MATHEMATICAL MORPHOLOGY , 2007 .

[104]  B. van Ginneken,et al.  Automated localization of the optic disc and the fovea , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[105]  Huiqi Li,et al.  Boundary detection of optic disk by a modified ASM method , 2003, Pattern Recognit..

[106]  M. J. Carreira,et al.  Localization and Extraction of the Optic Disc Using the Fuzzy Circular Hough Transform , 2006, ICAISC.

[107]  Jacob Scharcanski,et al.  Segmentation of the optic disk in color eye fundus images using an adaptive morphological approach , 2010, Comput. Biol. Medicine.

[108]  Dietrich Paulus,et al.  Vessel segmentation in retinal images , 2005, SPIE Medical Imaging.

[109]  Risto Myllylä,et al.  Automated segmentation of the macula by optical coherence tomography. , 2009, Optics express.

[110]  B. Thomas,et al.  Automated identification of diabetic retinal exudates in digital colour images , 2003, The British journal of ophthalmology.

[111]  Guoliang Fan,et al.  An efficient algorithm for extraction of anatomical structures in retinal images , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[112]  U. Rajendra Acharya,et al.  Identification of different stages of diabetic retinopathy using retinal optical images , 2008, Inf. Sci..

[113]  F. Zana,et al.  Robust segmentation of vessels from retinal angiography , 1997, Proceedings of 13th International Conference on Digital Signal Processing.

[114]  J. Thiran,et al.  Identification of the optic disk boundary in retinal images using active contours , 1999 .

[115]  George K. Matsopoulos,et al.  Detection of glaucomatous change based on vessel shape analysis , 2008, Comput. Medical Imaging Graph..

[116]  Pascale Massin,et al.  Automatic detection of microaneurysms in color fundus images , 2007, Medical Image Anal..

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

[118]  Juan Xu,et al.  Automated assessment of the optic nerve head on stereo disc photographs. , 2008, Investigative ophthalmology & visual science.

[119]  Albert C. S. Chung,et al.  Multi-scale model-based vessel enhancement using local line integrals , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[120]  Barry R. Masters,et al.  Fractal analysis of human retinal vessels , 1990, Other Conferences.

[121]  Bahram Khoobehi,et al.  Automatic Identification of Retinal Arteries and Veins From Dual-Wavelength Images Using Structural and Functional Features , 2007, IEEE Transactions on Biomedical Engineering.