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
Investigation of Federated Learning Algorithms for Retinal Optical Coherence Tomography Image Classification with Statistical Heterogeneity
Sanskar Amgain, Prashant Shrestha, Sophia Bano, Ignacio del Valle Torres, Michael Cunniffe, Victor Hernandez, Phil Beales, Binod Bhattarai
Less is more: Ensemble Learning for Retinal Disease Recognition Under Limited Resources
Jiahao Wang, Hong Peng, Shengchao Chen, Sufen Ren