Retinal layer parcellation of optical coherence tomography images: Data resource for multiple sclerosis and healthy controls
| Autor: | Sharon D. Solomon, Aaron Carass, Peter A. Calabresi, Jerry L. Prince, Shiv Saidha, Yufan He |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
genetic structures
Computer science lcsh:Computer applications to medicine. Medical informatics 03 medical and health sciences chemistry.chemical_compound Engineering 0302 clinical medicine Optical coherence tomography medicine Computer vision Layer (object-oriented design) lcsh:Science (General) 030304 developmental biology 0303 health sciences Retina Multidisciplinary medicine.diagnostic_test business.industry Multiple sclerosis Retinal Resource (Windows) medicine.disease eye diseases medicine.anatomical_structure chemistry lcsh:R858-859.7 Automatic segmentation sense organs Artificial intelligence business 030217 neurology & neurosurgery lcsh:Q1-390 |
| Zdroj: | Data in Brief, Vol 22, Iss, Pp 601-604 (2019) Data in Brief |
| ISSN: | 2352-3409 |
| Popis: | This paper presents optical coherence tomography (OCT) images of the human retina and manual delineations of eight retinal layers. The data includes 35 human retina scans acquired on a Spectralis OCT system (Heidelberg Engineering, Heidelberg, Germany), 14 of which are healthy controls (HC) and 21 have a diagnosis of multiple sclerosis (MS). The provided data includes manually delineation of eight retina layers, which were independently reviewed and edited. The data presented in this article was used to validate automatic segmentation algorithms (Lang et al., 2013). |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|