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
Visual Analytics for Early Detection of Retinal Diseases
Martin Röhlig, Oliver Stachs, Heidrun Schumann
Interpretable Diabetic Retinopathy Diagnosis based on Biomarker Activation Map
Pengxiao Zang, Tristan T. Hormel, Jie Wang, Yukun Guo, Steven T. Bailey, Christina J. Flaxel, David Huang, Thomas S. Hwang, Yali Jia
An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images
Yuhan Zheng, Fuping Wu, Bartłomiej W. Papież
CTT-Net: A Multi-view Cross-token Transformer for Cataract Postoperative Visual Acuity Prediction
Jinhong Wang, Jingwen Wang, Tingting Chen, Wenhao Zheng, Zhe Xu, Xingdi Wu, Wen Xu, Haochao Ying, Danny Chen, Jian Wu