Low rank based FAZ segmentation in OCTA images
Abstract Optical Coherence Tomography Angiography (OCTA) is a non-invasive method for vascular imaging of different tissues. Several diseases can disturb the blood supplying of retinal tissues which leads to loss of blood vessels and a reduction in the vascular density of retinal tissue. This also c...
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-07448-x |
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| author | Farnaz Sedighin Fatemeh Rezaei Maryam Monemian |
| author_facet | Farnaz Sedighin Fatemeh Rezaei Maryam Monemian |
| author_sort | Farnaz Sedighin |
| collection | DOAJ |
| description | Abstract Optical Coherence Tomography Angiography (OCTA) is a non-invasive method for vascular imaging of different tissues. Several diseases can disturb the blood supplying of retinal tissues which leads to loss of blood vessels and a reduction in the vascular density of retinal tissue. This also changes the size and shape of the FAZ (Fovea Avascular Zone) in the retinal OCTA images. Considering this fact, FAZ segmentation and analyzing its shape, can be used for diagnosing of several eye-related diseases. This paper is devoted to propose new methods for accurate segmentation of FAZ from OCTA images. The proposed methods have three steps: first, FAZ localization, for which, two methods have been proposed. The first one used Low-rank Tensor Ring (TR) decomposition of OCTA images and the other one exploited morphological operators. In the second step, the de-noised OCTA image is used for FAZ segmentation exploiting the information of FAZ localization, and in the third step, the resulting segmented FAZ is refined to derive a clean area. To the best of our knowledge, this is the first time of using low-rank TR estimation for FAZ segmentation. Simulation results confirmed the performance of the proposed methods for an accurate FAZ segmentation. |
| format | Article |
| id | doaj-art-408bca8a9949427a8f2d2d09a4e1b3a9 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-408bca8a9949427a8f2d2d09a4e1b3a92025-08-20T03:42:41ZengNature PortfolioScientific Reports2045-23222025-07-0115111310.1038/s41598-025-07448-xLow rank based FAZ segmentation in OCTA imagesFarnaz Sedighin0Fatemeh Rezaei1Maryam Monemian2Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical SciencesMedical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical SciencesMedical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical SciencesAbstract Optical Coherence Tomography Angiography (OCTA) is a non-invasive method for vascular imaging of different tissues. Several diseases can disturb the blood supplying of retinal tissues which leads to loss of blood vessels and a reduction in the vascular density of retinal tissue. This also changes the size and shape of the FAZ (Fovea Avascular Zone) in the retinal OCTA images. Considering this fact, FAZ segmentation and analyzing its shape, can be used for diagnosing of several eye-related diseases. This paper is devoted to propose new methods for accurate segmentation of FAZ from OCTA images. The proposed methods have three steps: first, FAZ localization, for which, two methods have been proposed. The first one used Low-rank Tensor Ring (TR) decomposition of OCTA images and the other one exploited morphological operators. In the second step, the de-noised OCTA image is used for FAZ segmentation exploiting the information of FAZ localization, and in the third step, the resulting segmented FAZ is refined to derive a clean area. To the best of our knowledge, this is the first time of using low-rank TR estimation for FAZ segmentation. Simulation results confirmed the performance of the proposed methods for an accurate FAZ segmentation.https://doi.org/10.1038/s41598-025-07448-xOptical coherence tomography angiographyFAZ segmentationLow-rank estimationTensor ring decomposition |
| spellingShingle | Farnaz Sedighin Fatemeh Rezaei Maryam Monemian Low rank based FAZ segmentation in OCTA images Scientific Reports Optical coherence tomography angiography FAZ segmentation Low-rank estimation Tensor ring decomposition |
| title | Low rank based FAZ segmentation in OCTA images |
| title_full | Low rank based FAZ segmentation in OCTA images |
| title_fullStr | Low rank based FAZ segmentation in OCTA images |
| title_full_unstemmed | Low rank based FAZ segmentation in OCTA images |
| title_short | Low rank based FAZ segmentation in OCTA images |
| title_sort | low rank based faz segmentation in octa images |
| topic | Optical coherence tomography angiography FAZ segmentation Low-rank estimation Tensor ring decomposition |
| url | https://doi.org/10.1038/s41598-025-07448-x |
| work_keys_str_mv | AT farnazsedighin lowrankbasedfazsegmentationinoctaimages AT fatemehrezaei lowrankbasedfazsegmentationinoctaimages AT maryammonemian lowrankbasedfazsegmentationinoctaimages |