Modelling of retinal vasculature based on genetically tuned parametric L-system
Structures of retinal blood vessels are of great importance in diagnosis and treatment of diseases that affect the eyes. Parametric Lindenmayer system (L-system) is one of the powerful rule-based methods that has a great capability for generating tree-like structures using simple rewriting rules. In...
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| Format: | Article |
| Language: | English |
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The Royal Society
2018-01-01
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| Series: | Royal Society Open Science |
| Subjects: | |
| Online Access: | https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.171639 |
| _version_ | 1818295097982189568 |
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| author | Seyed Mohammad Ali Aghamirmohammadali Ramin Bozorgmehry Boozarjomehry Mohammad Abdekhodaie |
| author_facet | Seyed Mohammad Ali Aghamirmohammadali Ramin Bozorgmehry Boozarjomehry Mohammad Abdekhodaie |
| author_sort | Seyed Mohammad Ali Aghamirmohammadali |
| collection | DOAJ |
| description | Structures of retinal blood vessels are of great importance in diagnosis and treatment of diseases that affect the eyes. Parametric Lindenmayer system (L-system) is one of the powerful rule-based methods that has a great capability for generating tree-like structures using simple rewriting rules. In this study, a novel framework, which can be used to model the retinal vasculature based on available images, has been proposed. This framework presents a solution to special instance of a general open problem, the L-system inverse problem, in which L-system rules should be obtained based on images representing a particular tree-like structure. In this study, genetic algorithm with a novel objective function based on feature matching and an L-system grammar comparison has been used along with nonlinear regression to solve the parametric L-system inverse problem. The resulting L-system growth rules have been employed to predict inaccessible vascular branches. Graphical and quantitative comparison between model results and target structures of different case studies reveals that the proposed framework can be used to generate the structure of retinal blood vessels accurately. Even in the cases lacking sufficient image data, it can provide acceptable predictions. |
| first_indexed | 2024-12-13T03:42:14Z |
| format | Article |
| id | doaj.art-b52b55baaa0443f8900f7ef6a4e03ff2 |
| institution | Directory Open Access Journal |
| issn | 2054-5703 |
| language | English |
| last_indexed | 2024-12-13T03:42:14Z |
| publishDate | 2018-01-01 |
| publisher | The Royal Society |
| record_format | Article |
| series | Royal Society Open Science |
| spelling | doaj.art-b52b55baaa0443f8900f7ef6a4e03ff22022-12-22T00:00:56ZengThe Royal SocietyRoyal Society Open Science2054-57032018-01-015510.1098/rsos.171639171639Modelling of retinal vasculature based on genetically tuned parametric L-systemSeyed Mohammad Ali AghamirmohammadaliRamin Bozorgmehry BoozarjomehryMohammad AbdekhodaieStructures of retinal blood vessels are of great importance in diagnosis and treatment of diseases that affect the eyes. Parametric Lindenmayer system (L-system) is one of the powerful rule-based methods that has a great capability for generating tree-like structures using simple rewriting rules. In this study, a novel framework, which can be used to model the retinal vasculature based on available images, has been proposed. This framework presents a solution to special instance of a general open problem, the L-system inverse problem, in which L-system rules should be obtained based on images representing a particular tree-like structure. In this study, genetic algorithm with a novel objective function based on feature matching and an L-system grammar comparison has been used along with nonlinear regression to solve the parametric L-system inverse problem. The resulting L-system growth rules have been employed to predict inaccessible vascular branches. Graphical and quantitative comparison between model results and target structures of different case studies reveals that the proposed framework can be used to generate the structure of retinal blood vessels accurately. Even in the cases lacking sufficient image data, it can provide acceptable predictions.https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.171639retinal vasculatureparametric l-systeml-system inverse problemmathematical morphology |
| spellingShingle | Seyed Mohammad Ali Aghamirmohammadali Ramin Bozorgmehry Boozarjomehry Mohammad Abdekhodaie Modelling of retinal vasculature based on genetically tuned parametric L-system Royal Society Open Science retinal vasculature parametric l-system l-system inverse problem mathematical morphology |
| title | Modelling of retinal vasculature based on genetically tuned parametric L-system |
| title_full | Modelling of retinal vasculature based on genetically tuned parametric L-system |
| title_fullStr | Modelling of retinal vasculature based on genetically tuned parametric L-system |
| title_full_unstemmed | Modelling of retinal vasculature based on genetically tuned parametric L-system |
| title_short | Modelling of retinal vasculature based on genetically tuned parametric L-system |
| title_sort | modelling of retinal vasculature based on genetically tuned parametric l system |
| topic | retinal vasculature parametric l-system l-system inverse problem mathematical morphology |
| url | https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.171639 |
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