TY - JOUR
AU - 
AB - Research Article Vol. 10, No. 12 / 1 December 2019 / Biomedical Optics Express 6057 Deep learning for quality assessment of retinal OCT images 1,2,7 3,7 1,2 J I N G WA N G, G U O H UA D E N G, WA N Y U E L I, Y I W E I 2 2 4,5 2,8 2,6,9 C H E N, F E N G G AO, H U L I U, Y I H E, A N D G U O H UA S H I University of Science and Technology of China, Hefei 230026, China Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215263, China Department of Ophthalmology, the Third People’s Hospital of Changzhou, Changzhou 213001, China The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China Jiangsu Province Hospital, Nanjing 210029, China CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai 200031, China These authors contributed to the work equally and should be considered as co-first authors heyi@sibet.ac.cn ghshi_lab@126.com Abstract: Optical coherence tomography (OCT) is a promising high-speed, non-invasive imaging modality providing high-resolution retinal scans. However, a variety of external 
TI - Deep learning for quality assessment of retinal OCT images
JF - Biomedical Optics Express
DO - 10.1364/boe.10.006057
DA - 2019-11-04
UR - https://www.deepdyve.com/lp/unpaywall/deep-learning-for-quality-assessment-of-retinal-oct-images-BpghAvBmx6
DP - DeepDyve
ER -