Toward ground-truth optical coherence tomography via three-dimensional unsupervised deep learning processing and data
R Wu, F Zheng, M Li, S Huang, X Ge… - … on Medical Imaging, 2024 - ieeexplore.ieee.org
Optical coherence tomography (OCT) can perform non-invasive high-resolution three-
dimensional (3D) imaging and has been widely used in biomedical fields, while it is …
dimensional (3D) imaging and has been widely used in biomedical fields, while it is …
Self-supervised Self2Self denoising strategy for OCT speckle reduction with a single noisy image
C Ge, X Yu, M Yuan, Z Fan, J Chen… - Biomedical Optics …, 2024 - opg.optica.org
Optical coherence tomography (OCT) inevitably suffers from the influence of speckles
originating from multiple scattered photons owing to its low-coherence interferometry …
originating from multiple scattered photons owing to its low-coherence interferometry …
Deep learning with adaptive convolutions for classification of retinal diseases via optical coherence tomography
K Karthik, M Mahadevappa - Image and Vision Computing, 2024 - Elsevier
Optical coherence tomography (OCT) uses interferometry to capture high-resolution cross-
sectional images of the retina to diagnose retinal diseases. Convolutional neural networks …
sectional images of the retina to diagnose retinal diseases. Convolutional neural networks …
A lightweight model for the retinal disease classification using optical coherence tomography
H Pan, J Miao, J Yu, J Dong, M Zhang, X Wang… - … Signal Processing and …, 2025 - Elsevier
Retinal diseases such as age-related macular degeneration and diabetic macular edema
will lead to irreversible blindness without timely diagnosis and treatment. Optical coherence …
will lead to irreversible blindness without timely diagnosis and treatment. Optical coherence …
Unsupervised OCT image despeckling with ground-truth-and repeated-scanning-free features
R Wu, S Huang, J Zhong, F Zheng, M Li, X Ge… - Optics …, 2024 - opg.optica.org
Optical coherence tomography (OCT) can resolve biological three-dimensional tissue
structures, but it is inevitably plagued by speckle noise that degrades image quality and …
structures, but it is inevitably plagued by speckle noise that degrades image quality and …
Noise-imitation learning: unpaired speckle noise reduction for optical coherence tomography
Objective. Optical coherence tomography (OCT) is widely used in clinical practice for its non-
invasive, high-resolution imaging capabilities. However, speckle noise inherent to its low …
invasive, high-resolution imaging capabilities. However, speckle noise inherent to its low …
Dual blind-spot network for self-supervised denoising in OCT images
The blind-spot network and its variants have shown promising results in the field of self-
supervised denoising tasks. These methods aim at concealing noisy image pixels and …
supervised denoising tasks. These methods aim at concealing noisy image pixels and …
Self-supervised Denoising and Bulk Motion Artifact Removal of 3D Optical Coherence Tomography Angiography of Awake Brain
Abstract Denoising of 3D Optical Coherence Tomography Angiography (OCTA) for awake
brain microvasculature is challenging. An OCTA volume is scanned slice by slice, with each …
brain microvasculature is challenging. An OCTA volume is scanned slice by slice, with each …
DBSN: Self-supervised Denoising for OCT Images via Dual Blind Strategy and Blind-Spot Network
C Ge, X Yu, M Li - 2023 IEEE 11th International Conference …, 2023 - ieeexplore.ieee.org
Blind-spot network and its variants have shown promising results in self-supervised
denoising tasks. The aim of these methods is to conceal pixels of noisy image and use self …
denoising tasks. The aim of these methods is to conceal pixels of noisy image and use self …
Axial Super-Resolution by Optical Coherence Tomography Spectrum-Based Training
Z Xu, Y Gao, X Chen, K Lin, L Liu - Available at SSRN 4835618 - papers.ssrn.com
Higher axial resolution for optical coherence tomography (OCT) images are always desired.
Deep learning has emerged as a powerful tool for image resolution enhancement, yet its …
Deep learning has emerged as a powerful tool for image resolution enhancement, yet its …