Analysis of normal human retinal vascular network architecture using multifractal geometry
AIM:To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.METHODS:Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca,Romania,between January 2012...
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Published in | International journal of ophthalmology Vol. 10; no. 3; pp. 434 - 438 |
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Format | Journal Article |
Language | English |
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China
International Journal of Ophthalmology Press
18.03.2017
Press of International Journal of Ophthalmology (IJO PRESS) |
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Abstract | AIM:To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.METHODS:Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca,Romania,between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images,corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms,applying the standard boxcounting method. Statistical analyses were performed using the Graph Pad In Stat software.RESULTS:The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions(D_q)for q=0,1,2,the width of the multifractal spectrum(Δα=α_(max)-α_(min))and the spectrum arms' heights difference(│Δf│)of the normal images were expressed as mean±standard deviation(SD):for segmented versions,D_0=1.7014±0.0057; D_1=1.6507±0.0058; D_2=1.5772±0.0059; Δα=0.92441±0.0085; │Δf│= 0.1453±0.0051; for skeletonised versions,D_0=1.6303±0.0051; D_1=1.6012±0.0059; D_2=1.5531± 0.0058; Δα=0.65032±0.0162; │Δf│= 0.0238±0.0161. The average of generalized dimensions(D_q)for q=0,1,2,the width of the multifractal spectrum(Δα)and the spectrum arms' heights difference(│Δf│)of the segmented versions was slightly greater than the skeletonised versions.CONCLUSION:The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases. |
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AbstractList | AIM: To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina. METHODS: Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images, corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms, applying the standard box-counting method. Statistical analyses were performed using the GraphPad InStat software. RESULTS: The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions (Dq) for q=0, 1, 2, the width of the multifractal spectrum (Δα=αmax - αmin) and the spectrum arms’ heights difference (│Δf│) of the normal images were expressed as mean±standard deviation (SD): for segmented versions, D0=1.7014±0.0057; D1=1.6507±0.0058; D2=1.5772±0.0059; Δα=0.92441±0.0085; │Δf│= 0.1453±0.0051; for skeletonised versions, D0=1.6303±0.0051; D1=1.6012±0.0059; D2=1.5531±0.0058; Δα=0.65032±0.0162; │Δf│= 0.0238±0.0161. The average of generalized dimensions (Dq) for q=0, 1, 2, the width of the multifractal spectrum (Δα) and the spectrum arms’ heights difference (│Δf│) of the segmented versions was slightly greater than the skeletonised versions. CONCLUSION: The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases. To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina. Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images, corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms, applying the standard box-counting method. Statistical analyses were performed using the GraphPad InStat software. The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions ( ) for =0, 1, 2, the width of the multifractal spectrum ( - ) and the spectrum arms' heights difference ( ) of the normal images were expressed as mean±standard deviation (SD): for segmented versions, =1.7014±0.0057; =1.6507±0.0058; =1.5772±0.0059; =0.92441±0.0085; = 0.1453±0.0051; for skeletonised versions, =1.6303±0.0051; =1.6012±0.0059; =1.5531±0.0058; =0.65032±0.0162; = 0.0238±0.0161. The average of generalized dimensions ( ) for =0, 1, 2, the width of the multifractal spectrum ( ) and the spectrum arms' heights difference ( ) of the segmented versions was slightly greater than the skeletonised versions. The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases. To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.AIMTo apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images, corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms, applying the standard box-counting method. Statistical analyses were performed using the GraphPad InStat software.METHODSFifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images, corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms, applying the standard box-counting method. Statistical analyses were performed using the GraphPad InStat software.The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions (Dq ) for q=0, 1, 2, the width of the multifractal spectrum (Δα=αmax - αmin ) and the spectrum arms' heights difference (|Δf|) of the normal images were expressed as mean±standard deviation (SD): for segmented versions, D0 =1.7014±0.0057; D1 =1.6507±0.0058; D2 =1.5772±0.0059; Δα=0.92441±0.0085; |Δf|= 0.1453±0.0051; for skeletonised versions, D0 =1.6303±0.0051; D1 =1.6012±0.0059; D2 =1.5531±0.0058; Δα=0.65032±0.0162; |Δf|= 0.0238±0.0161. The average of generalized dimensions (Dq ) for q=0, 1, 2, the width of the multifractal spectrum (Δα) and the spectrum arms' heights difference (|Δf|) of the segmented versions was slightly greater than the skeletonised versions.RESULTSThe architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions (Dq ) for q=0, 1, 2, the width of the multifractal spectrum (Δα=αmax - αmin ) and the spectrum arms' heights difference (|Δf|) of the normal images were expressed as mean±standard deviation (SD): for segmented versions, D0 =1.7014±0.0057; D1 =1.6507±0.0058; D2 =1.5772±0.0059; Δα=0.92441±0.0085; |Δf|= 0.1453±0.0051; for skeletonised versions, D0 =1.6303±0.0051; D1 =1.6012±0.0059; D2 =1.5531±0.0058; Δα=0.65032±0.0162; |Δf|= 0.0238±0.0161. The average of generalized dimensions (Dq ) for q=0, 1, 2, the width of the multifractal spectrum (Δα) and the spectrum arms' heights difference (|Δf|) of the segmented versions was slightly greater than the skeletonised versions.The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases.CONCLUSIONThe multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases. AIM:To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.METHODS:Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca,Romania,between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images,corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms,applying the standard boxcounting method. Statistical analyses were performed using the Graph Pad In Stat software.RESULTS:The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions(D_q)for q=0,1,2,the width of the multifractal spectrum(Δα=α_(max)-α_(min))and the spectrum arms' heights difference(│Δf│)of the normal images were expressed as mean±standard deviation(SD):for segmented versions,D_0=1.7014±0.0057; D_1=1.6507±0.0058; D_2=1.5772±0.0059; Δα=0.92441±0.0085; │Δf│= 0.1453±0.0051; for skeletonised versions,D_0=1.6303±0.0051; D_1=1.6012±0.0059; D_2=1.5531± 0.0058; Δα=0.65032±0.0162; │Δf│= 0.0238±0.0161. The average of generalized dimensions(D_q)for q=0,1,2,the width of the multifractal spectrum(Δα)and the spectrum arms' heights difference(│Δf│)of the segmented versions was slightly greater than the skeletonised versions.CONCLUSION:The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases. |
Author | tefan ??lu Sebastian Stach Dan Mihai C?lug?ru Carmen Alina Lupa?cu Simona Delia Nicoar |
AuthorAffiliation | Discipline of Descriptive Geometry and Engineering Gra- phics, Department of AET, Faculty of Mechanical Engineering, Technical University of Cluj-Napoca, 103-105 B-dul Muncii St., Cluj-Napoca 400641, Cluj, Romania Department of Biomedical Computer Systems, Institute of Informatics, Faculty of Computer Science and Materials Science, University of Silesia, Bedzifiska 39, 41-205 Sosnowiec, Poland Discipline of Ophthalmology, Department of Surgical Speci- alties and Medical Imaging, Faculty of Medicine, "Iuliu Halie- ganu" University of Medicine and Pharmacy Cluj-Napoca, 8 Victor Babes St., Cluj-Napoca 400012, Cluj, Romania Department of Mathematics and Informatics, University of Palermo, Via Archirafi 34, Palermo 90123, Italy |
AuthorAffiliation_xml | – name: 3 Discipline of Ophthalmology, Department of Surgical Specialties and Medical Imaging, Faculty of Medicine, “Iuliu Haţieganu” University of Medicine and Pharmacy Cluj-Napoca, 8 Victor Babeş St., Cluj-Napoca 400012, Cluj, Romania – name: 1 Discipline of Descriptive Geometry and Engineering Graphics, Department of AET, Faculty of Mechanical Engineering, Technical University of Cluj-Napoca, 103-105 B-dul Muncii St., Cluj-Napoca 400641, Cluj, Romania – name: 4 Department of Mathematics and Informatics, University of Palermo, Via Archirafi 34, Palermo 90123, Italy – name: 2 Department of Biomedical Computer Systems, Institute of Informatics, Faculty of Computer Science and Materials Science, University of Silesia, Będzińska 39, 41-205 Sosnowiec, Poland |
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Notes | generalized dimensions multifractal retinal vessel segmentation retinal image analysis retinal microvasculature standard box-counting method AIM:To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.METHODS:Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca,Romania,between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images,corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms,applying the standard boxcounting method. Statistical analyses were performed using the Graph Pad In Stat software.RESULTS:The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions(D_q)for q=0,1,2,the width of the multifractal spectrum(Δα=α_(max)-α_(min))and the spectrum arms' heights difference(│Δf│)of the normal images were expressed as mean±standard deviation(SD):for segmented versions,D_0=1.7014±0.0057; D_1=1.6507±0.0058; D_2=1.5772±0.0059; Δα=0.92441±0.0085; │Δf│= 0.1453±0.0051; for skeletonised versions,D_0=1.6303±0.0051; D_1=1.6012±0.0059; D_2=1.5531± 0.0058; Δα=0.65032±0.0162; │Δf│= 0.0238±0.0161. The average of generalized dimensions(D_q)for q=0,1,2,the width of the multifractal spectrum(Δα)and the spectrum arms' heights difference(│Δf│)of the segmented versions was slightly greater than the skeletonised versions.CONCLUSION:The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
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SubjectTerms | Clinical Research generalized dimensions multifractal retinal image analysis retinal microvasculature retinal vessel segmentation standard box-counting method |
Title | Analysis of normal human retinal vascular network architecture using multifractal geometry |
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