OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods
Abstract Optical coherence tomography (OCT) is a non-invasive imaging technique with extensive clinical applications in ophthalmology. OCT enables the visualization of the retinal layers, playing a vital role in the early detection and monitoring of retinal diseases. OCT uses the principle of light...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-04-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-03182-7 |
| _version_ | 1797209523898810368 |
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| author | Mikhail Kulyabin Aleksei Zhdanov Anastasia Nikiforova Andrey Stepichev Anna Kuznetsova Mikhail Ronkin Vasilii Borisov Alexander Bogachev Sergey Korotkich Paul A. Constable Andreas Maier |
| author_facet | Mikhail Kulyabin Aleksei Zhdanov Anastasia Nikiforova Andrey Stepichev Anna Kuznetsova Mikhail Ronkin Vasilii Borisov Alexander Bogachev Sergey Korotkich Paul A. Constable Andreas Maier |
| author_sort | Mikhail Kulyabin |
| collection | DOAJ |
| description | Abstract Optical coherence tomography (OCT) is a non-invasive imaging technique with extensive clinical applications in ophthalmology. OCT enables the visualization of the retinal layers, playing a vital role in the early detection and monitoring of retinal diseases. OCT uses the principle of light wave interference to create detailed images of the retinal microstructures, making it a valuable tool for diagnosing ocular conditions. This work presents an open-access OCT dataset (OCTDL) comprising over 2000 OCT images labeled according to disease group and retinal pathology. The dataset consists of OCT records of patients with Age-related Macular Degeneration (AMD), Diabetic Macular Edema (DME), Epiretinal Membrane (ERM), Retinal Artery Occlusion (RAO), Retinal Vein Occlusion (RVO), and Vitreomacular Interface Disease (VID). The images were acquired with an Optovue Avanti RTVue XR using raster scanning protocols with dynamic scan length and image resolution. Each retinal b-scan was acquired by centering on the fovea and interpreted and cataloged by an experienced retinal specialist. In this work, we applied Deep Learning classification techniques to this new open-access dataset. |
| first_indexed | 2024-04-24T09:56:04Z |
| format | Article |
| id | doaj.art-0f7c054c7a7847dc81b3b0758fa57e77 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-04-24T09:56:04Z |
| publishDate | 2024-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-0f7c054c7a7847dc81b3b0758fa57e772024-04-14T11:07:37ZengNature PortfolioScientific Data2052-44632024-04-0111111010.1038/s41597-024-03182-7OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning MethodsMikhail Kulyabin0Aleksei Zhdanov1Anastasia Nikiforova2Andrey Stepichev3Anna Kuznetsova4Mikhail Ronkin5Vasilii Borisov6Alexander Bogachev7Sergey Korotkich8Paul A. Constable9Andreas Maier10Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-NürnbergEngineering School of Information Technologies, Telecommunications and Control Systems, Ural Federal University Named after the First President of Russia B. N. YeltsinOphthalmosurgery Clinic “Professorskaya Plus”Ophthalmosurgery Clinic “Professorskaya Plus”Ophthalmosurgery Clinic “Professorskaya Plus”Engineering School of Information Technologies, Telecommunications and Control Systems, Ural Federal University Named after the First President of Russia B. N. YeltsinEngineering School of Information Technologies, Telecommunications and Control Systems, Ural Federal University Named after the First President of Russia B. N. YeltsinOphthalmosurgery Clinic “Professorskaya Plus”Ophthalmosurgery Clinic “Professorskaya Plus”Flinders University, College of Nursing and Health Sciences, Caring Futures InstitutePattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-NürnbergAbstract Optical coherence tomography (OCT) is a non-invasive imaging technique with extensive clinical applications in ophthalmology. OCT enables the visualization of the retinal layers, playing a vital role in the early detection and monitoring of retinal diseases. OCT uses the principle of light wave interference to create detailed images of the retinal microstructures, making it a valuable tool for diagnosing ocular conditions. This work presents an open-access OCT dataset (OCTDL) comprising over 2000 OCT images labeled according to disease group and retinal pathology. The dataset consists of OCT records of patients with Age-related Macular Degeneration (AMD), Diabetic Macular Edema (DME), Epiretinal Membrane (ERM), Retinal Artery Occlusion (RAO), Retinal Vein Occlusion (RVO), and Vitreomacular Interface Disease (VID). The images were acquired with an Optovue Avanti RTVue XR using raster scanning protocols with dynamic scan length and image resolution. Each retinal b-scan was acquired by centering on the fovea and interpreted and cataloged by an experienced retinal specialist. In this work, we applied Deep Learning classification techniques to this new open-access dataset.https://doi.org/10.1038/s41597-024-03182-7 |
| spellingShingle | Mikhail Kulyabin Aleksei Zhdanov Anastasia Nikiforova Andrey Stepichev Anna Kuznetsova Mikhail Ronkin Vasilii Borisov Alexander Bogachev Sergey Korotkich Paul A. Constable Andreas Maier OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods Scientific Data |
| title | OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods |
| title_full | OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods |
| title_fullStr | OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods |
| title_full_unstemmed | OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods |
| title_short | OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods |
| title_sort | octdl optical coherence tomography dataset for image based deep learning methods |
| url | https://doi.org/10.1038/s41597-024-03182-7 |
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