3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images
Spectral-Domain Optical Coherence Tomography (SD-OCT) is a widely used interferometric diagnostic technique in ophthalmology that provides novel in vivo information of depth-resolved inner and outer retinal structures. This imaging modality can assist clinicians in monitoring the progression of Age-...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2017/4362603 |
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| author | M. Esmaeili A. M. Dehnavi H. Rabbani |
| author_facet | M. Esmaeili A. M. Dehnavi H. Rabbani |
| author_sort | M. Esmaeili |
| collection | DOAJ |
| description | Spectral-Domain Optical Coherence Tomography (SD-OCT) is a widely used interferometric diagnostic technique in ophthalmology that provides novel in vivo information of depth-resolved inner and outer retinal structures. This imaging modality can assist clinicians in monitoring the progression of Age-related Macular Degeneration (AMD) by providing high-resolution visualization of drusen. Quantitative tools for assessing drusen volume that are indicative of AMD progression may lead to appropriate metrics for selecting treatment protocols. To address this need, a fully automated algorithm was developed to segment drusen area and volume from SD-OCT images. The proposed algorithm consists of three parts: (1) preprocessing, which includes creating binary mask and removing possible highly reflective posterior hyaloid that is used in accurate detection of inner segment/outer segment (IS/OS) junction layer and Bruch’s membrane (BM) retinal layers; (2) coarse segmentation, in which 3D curvelet transform and graph theory are employed to get the possible candidate drusenoid regions; (3) fine segmentation, in which morphological operators are used to remove falsely extracted elongated structures and get the refined segmentation results. The proposed method was evaluated in 20 publically available volumetric scans acquired by using Bioptigen spectral-domain ophthalmic imaging system. The average true positive and false positive volume fractions (TPVF and FPVF) for the segmentation of drusenoid regions were found to be 89.15% ± 3.76 and 0.17% ± .18%, respectively. |
| format | Article |
| id | doaj-art-47e9e6f6785443ef90401c8734908f86 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
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| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-47e9e6f6785443ef90401c8734908f862025-02-03T05:45:18ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552017-01-01201710.1155/2017/436260343626033D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography ImagesM. Esmaeili0A. M. Dehnavi1H. Rabbani2Department of Bioelectrics and Biomedical Engineering, Medical Image & Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, IranDepartment of Bioelectrics and Biomedical Engineering, Medical Image & Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, IranDepartment of Bioelectrics and Biomedical Engineering, Medical Image & Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, IranSpectral-Domain Optical Coherence Tomography (SD-OCT) is a widely used interferometric diagnostic technique in ophthalmology that provides novel in vivo information of depth-resolved inner and outer retinal structures. This imaging modality can assist clinicians in monitoring the progression of Age-related Macular Degeneration (AMD) by providing high-resolution visualization of drusen. Quantitative tools for assessing drusen volume that are indicative of AMD progression may lead to appropriate metrics for selecting treatment protocols. To address this need, a fully automated algorithm was developed to segment drusen area and volume from SD-OCT images. The proposed algorithm consists of three parts: (1) preprocessing, which includes creating binary mask and removing possible highly reflective posterior hyaloid that is used in accurate detection of inner segment/outer segment (IS/OS) junction layer and Bruch’s membrane (BM) retinal layers; (2) coarse segmentation, in which 3D curvelet transform and graph theory are employed to get the possible candidate drusenoid regions; (3) fine segmentation, in which morphological operators are used to remove falsely extracted elongated structures and get the refined segmentation results. The proposed method was evaluated in 20 publically available volumetric scans acquired by using Bioptigen spectral-domain ophthalmic imaging system. The average true positive and false positive volume fractions (TPVF and FPVF) for the segmentation of drusenoid regions were found to be 89.15% ± 3.76 and 0.17% ± .18%, respectively.http://dx.doi.org/10.1155/2017/4362603 |
| spellingShingle | M. Esmaeili A. M. Dehnavi H. Rabbani 3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images Journal of Electrical and Computer Engineering |
| title | 3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images |
| title_full | 3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images |
| title_fullStr | 3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images |
| title_full_unstemmed | 3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images |
| title_short | 3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images |
| title_sort | 3d curvelet based segmentation and quantification of drusen in optical coherence tomography images |
| url | http://dx.doi.org/10.1155/2017/4362603 |
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