Optical coherence tomography and glaucoma

A Geevarghese, G Wollstein, H Ishikawa… - Annual review of …, 2021 - annualreviews.org
Early detection and monitoring are critical to the diagnosis and management of glaucoma, a
progressive optic neuropathy that causes irreversible blindness. Optical coherence …

Deep learning in electron microscopy

JM Ede - Machine Learning: Science and Technology, 2021 - iopscience.iop.org
Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

[HTML][HTML] SDnDTI: Self-supervised deep learning-based denoising for diffusion tensor MRI

Q Tian, Z Li, Q Fan, JR Polimeni, B Bilgic, DH Salat… - Neuroimage, 2022 - Elsevier
Diffusion tensor magnetic resonance imaging (DTI) is a widely adopted neuroimaging
method for the in vivo mapping of brain tissue microstructure and white matter tracts …

Simultaneous denoising and super-resolution of optical coherence tomography images based on generative adversarial network

Y Huang, Z Lu, Z Shao, M Ran, J Zhou, L Fang… - Optics express, 2019 - opg.optica.org
Optical coherence tomography (OCT) has become a very promising diagnostic method in
clinical practice, especially for ophthalmic diseases. However, speckle noise and low …

[HTML][HTML] Endpoints for clinical trials in ophthalmology

L Schmetterer, H Scholl, G Garhöfer… - Progress in Retinal and …, 2023 - Elsevier
With the identification of novel targets, the number of interventional clinical trials in
ophthalmology has increased. Visual acuity has for a long time been considered the gold …

Glaucoma management in the era of artificial intelligence

SK Devalla, Z Liang, TH Pham, C Boote… - British Journal of …, 2020 - bjo.bmj.com
Glaucoma is a result of irreversible damage to the retinal ganglion cells. While an early
intervention could minimise the risk of vision loss in glaucoma, its asymptomatic nature …

Noise-powered disentangled representation for unsupervised speckle reduction of optical coherence tomography images

Y Huang, W Xia, Z Lu, Y Liu, H Chen… - … on Medical Imaging, 2020 - ieeexplore.ieee.org
Due to its noninvasive character, optical coherence tomography (OCT) has become a
popular diagnostic method in clinical settings. However, the low-coherence interferometric …

SiameseGAN: a generative model for denoising of spectral domain optical coherence tomography images

NA Kande, R Dakhane, A Dukkipati… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Optical coherence tomography (OCT) is a standard diagnostic imaging method for
assessment of ophthalmic diseases. The speckle noise present in the high-speed OCT …

Real-time noise reduction based on ground truth free deep learning for optical coherence tomography

Y Huang, N Zhang, Q Hao - Biomedical Optics Express, 2021 - opg.optica.org
Optical coherence tomography (OCT) is a high-resolution non-invasive 3D imaging
modality, which has been widely used for biomedical research and clinical studies. The …

Comparative study of deep neural networks with unsupervised Noise2Noise strategy for noise reduction of optical coherence tomography images

B Qiu, S Zeng, X Meng, Z Jiang, Y You… - Journal of …, 2021 - Wiley Online Library
As a powerful diagnostic tool, optical coherence tomography (OCT) has been widely used in
various clinical setting. However, OCT images are susceptible to inherent speckle noise that …