Deep learning in retinal optical coherence tomography (OCT): A comprehensive survey
Retinal optical coherence tomography (OCT) images provide fundamental information
regarding the health of the posterior eye (eg, the retina and choroid). Thus, the development …
regarding the health of the posterior eye (eg, the retina and choroid). Thus, the development …
Deep learning in biomedical optics
This article reviews deep learning applications in biomedical optics with a particular
emphasis on image formation. The review is organized by imaging domains within …
emphasis on image formation. The review is organized by imaging domains within …
Multi-scale convolutional neural network for automated AMD classification using retinal OCT images
Background and objective Age-related macular degeneration (AMD) is the most common
cause of blindness in developed countries, especially in people over 60 years of age. The …
cause of blindness in developed countries, especially in people over 60 years of age. The …
Deep learning protocol for improved photoacoustic brain imaging
One of the key limitations for the clinical translation of photoacoustic imaging is penetration
depth that is linked to the tissue maximum permissible exposures (MPE) recommended by …
depth that is linked to the tissue maximum permissible exposures (MPE) recommended by …
[HTML][HTML] A hybrid framework based on extreme learning machine, discrete wavelet transform, and autoencoder with feature penalty for stock prediction
Accurate prediction of the stock market trend can assist efficient portfolio and risk
management. In recent years, with the rapid development of deep learning, it can make the …
management. In recent years, with the rapid development of deep learning, it can make the …
[HTML][HTML] Synchrotron validation of inline coherent imaging for tracking laser keyhole depth
In situ monitoring is critical to the increasing adoption of laser powder bed fusion (LPBF) and
laser welding by industry for manufacture of complex metallic components. Optical …
laser welding by industry for manufacture of complex metallic components. Optical …
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 …
modality, which has been widely used for biomedical research and clinical studies. The …
Triplet cross-fusion learning for unpaired image denoising in optical coherence tomography
Optical coherence tomography (OCT) is a widely-used modality in clinical imaging, which
suffers from the speckle noise inevitably. Deep learning has proven its superior capability in …
suffers from the speckle noise inevitably. Deep learning has proven its superior capability in …
[HTML][HTML] Machine learning-based multi-objective optimization of concentrated solar thermal gasification of biomass incorporating life cycle assessment and techno …
The combination of solar and biomass energy systems is regarded as a highly promising
technology for tackling the challenges related to greenhouse gas emissions from energy …
technology for tackling the challenges related to greenhouse gas emissions from energy …
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 …
various clinical setting. However, OCT images are susceptible to inherent speckle noise that …