Deep learning-based image quality assessment for optical coherence tomography macular scans: a multicentre study.
Ziqi TangXi WangAn Ran RanDawei YangAnni LingJason C S YamXiujuan ZhangSimon K H SzetoJason ChanCherie Y K WongVivian W K HuiCarmen Kar Mun ChanTien-Yin WongChing-Yu ChengSabanayagam CharumathiYih-Chung ThamGerald LiewAnantharaman GiridharRajiv RamanYu CaiHaoxuan CheLuyang LuoQuande LiuYiu Lun WongAmanda K Y NgaiVincent L YuenNelson KeiTimothy Y Y LaiHao ChenClement Chee Yung ThamPheng-Ann HengCarol Yim-Lui CheungPublished in: The British journal of ophthalmology (2024)
Our models could be used for filtering out ungradable 3D scans and further incorporated with a disease-detection DL model, allowing a fully automated eye disease detection workflow.
Keyphrases
- deep learning
- optical coherence tomography
- image quality
- computed tomography
- loop mediated isothermal amplification
- dual energy
- machine learning
- diabetic retinopathy
- label free
- real time pcr
- artificial intelligence
- high throughput
- contrast enhanced
- convolutional neural network
- electronic health record
- cataract surgery
- quantum dots
- sensitive detection