Optical Coherence Tomography
Optical coherence tomography (OCT) is a non-invasive imaging technique providing high-resolution cross-sectional images of tissues, primarily used in ophthalmology but with expanding applications in other fields. Current research focuses on improving image quality through deep learning-based denoising and reconstruction methods, often employing U-Net and Transformer architectures, as well as developing advanced segmentation algorithms for precise identification of anatomical structures and biomarkers. These advancements are significantly impacting disease diagnosis and prognosis, particularly in retinal diseases like age-related macular degeneration and glaucoma, by enabling automated analysis and quantitative assessment of disease progression.
Papers
Eye Disease Prediction using Ensemble Learning and Attention on OCT Scans
Gauri Naik, Nandini Narvekar, Dimple Agarwal, Nishita Nandanwar, Himangi Pande
Self-supervised OCT Image Denoising with Slice-to-Slice Registration and Reconstruction
Shijie Li, Palaiologos Alexopoulos, Anse Vellappally, Ronald Zambrano, Wollstein Gadi, Guido Gerig
OCT2Confocal: 3D CycleGAN based Translation of Retinal OCT Images to Confocal Microscopy
Xin Tian, Nantheera Anantrasirichai, Lindsay Nicholson, Alin Achim
Leveraging Multimodal Fusion for Enhanced Diagnosis of Multiple Retinal Diseases in Ultra-wide OCTA
Hao Wei, Peilun Shi, Guitao Bai, Minqing Zhang, Shuangle Li, Wu Yuan
Back to Basics: Fast Denoising Iterative Algorithm
Deborah Pereg
Artificial Intelligence in Assessing Cardiovascular Diseases and Risk Factors via Retinal Fundus Images: A Review of the Last Decade
Mirsaeed Abdollahi, Ali Jafarizadeh, Amirhosein Ghafouri Asbagh, Navid Sobhi, Keysan Pourmoghtader, Siamak Pedrammehr, Houshyar Asadi, Roohallah Alizadehsani, Ru-San Tan, U. Rajendra Acharya