COph100: A comprehensive fundus image registration dataset from infants constituting the “RIDIRP” database
Abstract Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on adult retinal pathologies with high-quality images, have limited number of image pairs and neglect clinical challenges. To address this gap, w...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04426-w |
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| author | Yan Hu Mingdao Gong Zhongxi Qiu Jiabao Liu Hongli Shen Mingzhen Yuan Xiaoqing Zhang Heng Li Hai Lu Jiang Liu |
| author_facet | Yan Hu Mingdao Gong Zhongxi Qiu Jiabao Liu Hongli Shen Mingzhen Yuan Xiaoqing Zhang Heng Li Hai Lu Jiang Liu |
| author_sort | Yan Hu |
| collection | DOAJ |
| description | Abstract Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on adult retinal pathologies with high-quality images, have limited number of image pairs and neglect clinical challenges. To address this gap, we introduce COph100, a novel and challenging dataset known as the Comprehensive Ophthalmology Retinal Image Registration dataset for infants with a wide range of image quality issues constituting the public “RIDIRP” database. COph100 consists of 100 eyes, each with 2 to 9 examination sessions, amounting to a total of 491 image pairs carefully selected from the publicly available dataset. We manually labeled the corresponding ground truth image points and provided automatic vessel segmentation masks for each image. We have assessed COph100 in terms of image quality and registration outcomes using state-of-the-art algorithms. This resource enables a robust comparison of retinal registration methodologies and aids in the analysis of disease progression in infants, thereby deepening our understanding of pediatric ophthalmic conditions. |
| format | Article |
| id | doaj-art-8b0b8ad8b85e47f5a7ffe87d5f459fc9 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-8b0b8ad8b85e47f5a7ffe87d5f459fc92025-01-19T12:10:03ZengNature PortfolioScientific Data2052-44632025-01-0112111010.1038/s41597-025-04426-wCOph100: A comprehensive fundus image registration dataset from infants constituting the “RIDIRP” databaseYan Hu0Mingdao Gong1Zhongxi Qiu2Jiabao Liu3Hongli Shen4Mingzhen Yuan5Xiaoqing Zhang6Heng Li7Hai Lu8Jiang Liu9Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and TechnologyResearch Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and TechnologyResearch Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and TechnologyResearch Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and TechnologyResearch Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and TechnologyBeijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Sciences Key LaboratoryCenter for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics, Shenzhen Institute of Advanced Technology, Chinese Academy of SciencesResearch Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and TechnologyBeijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Sciences Key LaboratoryResearch Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering, Southern University of Science and TechnologyAbstract Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on adult retinal pathologies with high-quality images, have limited number of image pairs and neglect clinical challenges. To address this gap, we introduce COph100, a novel and challenging dataset known as the Comprehensive Ophthalmology Retinal Image Registration dataset for infants with a wide range of image quality issues constituting the public “RIDIRP” database. COph100 consists of 100 eyes, each with 2 to 9 examination sessions, amounting to a total of 491 image pairs carefully selected from the publicly available dataset. We manually labeled the corresponding ground truth image points and provided automatic vessel segmentation masks for each image. We have assessed COph100 in terms of image quality and registration outcomes using state-of-the-art algorithms. This resource enables a robust comparison of retinal registration methodologies and aids in the analysis of disease progression in infants, thereby deepening our understanding of pediatric ophthalmic conditions.https://doi.org/10.1038/s41597-025-04426-w |
| spellingShingle | Yan Hu Mingdao Gong Zhongxi Qiu Jiabao Liu Hongli Shen Mingzhen Yuan Xiaoqing Zhang Heng Li Hai Lu Jiang Liu COph100: A comprehensive fundus image registration dataset from infants constituting the “RIDIRP” database Scientific Data |
| title | COph100: A comprehensive fundus image registration dataset from infants constituting the “RIDIRP” database |
| title_full | COph100: A comprehensive fundus image registration dataset from infants constituting the “RIDIRP” database |
| title_fullStr | COph100: A comprehensive fundus image registration dataset from infants constituting the “RIDIRP” database |
| title_full_unstemmed | COph100: A comprehensive fundus image registration dataset from infants constituting the “RIDIRP” database |
| title_short | COph100: A comprehensive fundus image registration dataset from infants constituting the “RIDIRP” database |
| title_sort | coph100 a comprehensive fundus image registration dataset from infants constituting the ridirp database |
| url | https://doi.org/10.1038/s41597-025-04426-w |
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