Predicting Postoperative Vision for Macular Hole with Automated Image Analysis

Autor:	Morten la Cour, Amar Vijai Nasrulloh, Mark Alberti, Sara Graziado, Boguslaw Obara, Declan C Murphy, David H. W. Steel, Clare Lendrem
Rok vydání:	2020
Předmět:	Male medicine.medical_specialty genetic structures Visual Acuity Spectral domain Retina Image (mathematics) 03 medical and health sciences 0302 clinical medicine Imaging Three-Dimensional Optical coherence tomography Ophthalmology Vitrectomy Report 3D 3-dimensional SD-OCT spectral domain OCT Medicine Humans VA visual acuity Postoperative Period MH macular hole Macular hole 030304 developmental biology Aged 0303 health sciences medicine.diagnostic_test BD base diameter business.industry MLD minimum linear diameter Middle Aged medicine.disease Prognosis Retinal Perforations eye diseases AL axial length 030221 ophthalmology & optometry Female business Tomography Optical Coherence
Zdroj:	Ophthalmology. Retina Murphy, D C, Nasrulloh, A V, Lendrem, C, Graziado, S, Alberti, M, La Cour, M, Obara, B & Steel, D H W 2020, ' Predicting Postoperative Vision for Macular Hole with Automated Image Analysis ', Ophthalmology Retina, vol. 4, no. 12, pp. 1211-1213 . https://doi.org/10.1016/j.oret.2020.06.005
ISSN:	2468-6530
DOI:	10.1016/j.oret.2020.06.005
Popis:	Unstructured abstract A predictive model for the visual outcome after successful macular hole surgery using a prospectively collected dataset and automated image analysis of pre-operative spectral domain optical coherence tomography images is presented with an R2 of 45%.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f14c09bece8084168269a06faded63e https://pubmed.ncbi.nlm.nih.gov/32565385 Zobrazit plný text záznamu