OCTA-500 : A retinal dataset for optical coherence tomography angiography study
Copyright © 2024 Elsevier B.V. All rights reserved..
Optical coherence tomography angiography (OCTA) is a novel imaging modality that has been widely utilized in ophthalmology and neuroscience studies to observe retinal vessels and microvascular systems. However, publicly available OCTA datasets remain scarce. In this paper, we introduce the largest and most comprehensive OCTA dataset dubbed OCTA-500, which contains OCTA imaging under two fields of view (FOVs) from 500 subjects. The dataset provides rich images and annotations including two modalities (OCT/OCTA volumes), six types of projections, four types of text labels (age/gender/eye/disease) and seven types of segmentation labels (large vessel/capillary/artery/vein/2D FAZ/3D FAZ/retinal layers). Then, we propose a multi-object segmentation task called CAVF, which integrates capillary segmentation, artery segmentation, vein segmentation, and FAZ segmentation under a unified framework. In addition, we optimize the 3D-to-2D image projection network (IPN) to IPN-V2 to serve as one of the segmentation baselines. Experimental results demonstrate that IPN-V2 achieves an about 10% mIoU improvement over IPN on CAVF task. Finally, we further study the impact of several dataset characteristics: the training set size, the model input (OCT/OCTA, 3D volume/2D projection), the baseline networks, and the diseases. The dataset and code are publicly available at: https://ieee-dataport.org/open-access/octa-500.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:93 |
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| Enthalten in: |
Medical image analysis - 93(2024) vom: 05. März, Seite 103092 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Li, Mingchao [VerfasserIn] |
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| Anmerkungen: |
Date Completed 04.03.2024 Date Revised 04.03.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.media.2024.103092 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM368143902 |
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| 520 | |a Optical coherence tomography angiography (OCTA) is a novel imaging modality that has been widely utilized in ophthalmology and neuroscience studies to observe retinal vessels and microvascular systems. However, publicly available OCTA datasets remain scarce. In this paper, we introduce the largest and most comprehensive OCTA dataset dubbed OCTA-500, which contains OCTA imaging under two fields of view (FOVs) from 500 subjects. The dataset provides rich images and annotations including two modalities (OCT/OCTA volumes), six types of projections, four types of text labels (age/gender/eye/disease) and seven types of segmentation labels (large vessel/capillary/artery/vein/2D FAZ/3D FAZ/retinal layers). Then, we propose a multi-object segmentation task called CAVF, which integrates capillary segmentation, artery segmentation, vein segmentation, and FAZ segmentation under a unified framework. In addition, we optimize the 3D-to-2D image projection network (IPN) to IPN-V2 to serve as one of the segmentation baselines. Experimental results demonstrate that IPN-V2 achieves an about 10% mIoU improvement over IPN on CAVF task. Finally, we further study the impact of several dataset characteristics: the training set size, the model input (OCT/OCTA, 3D volume/2D projection), the baseline networks, and the diseases. The dataset and code are publicly available at: https://ieee-dataport.org/open-access/octa-500 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Medical image dataset | |
| 650 | 4 | |a OCTA | |
| 650 | 4 | |a Retina | |
| 650 | 4 | |a Segmentation | |
| 700 | 1 | |a Huang, Kun |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Qiuzhuo |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Jiadong |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Yuhan |e verfasserin |4 aut | |
| 700 | 1 | |a Ji, Zexuan |e verfasserin |4 aut | |
| 700 | 1 | |a Xie, Keren |e verfasserin |4 aut | |
| 700 | 1 | |a Yuan, Songtao |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Qinghuai |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Qiang |e verfasserin |4 aut | |
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