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

Publikováno v: 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

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 present

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f14c09bece8084168269a06faded63e
https://pubmed.ncbi.nlm.nih.gov/32565385