AIMC Topic: Deep Learning

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Extended scene deep learning wavefront sensing.

Journal of the Optical Society of America. A, Optics, image science, and vision
We have applied a combination of blind deconvolution and deep learning to the processing of Shack-Hartmann images. By using the intensity information contained in spot positions, and the fine structure of the separate images created by the lenslets, ...

Performance comparison of image enhancers with and without deep learning.

Journal of the Optical Society of America. A, Optics, image science, and vision
Image enhancement is a computational procedure to improve visibility of details and content of an input image. Several image enhancement algorithms have been developed thus far, from traditional methods that process a single image based on physical m...

Potential SARS-CoV-2 nonstructural proteins inhibitors: drugs repurposing with drug-target networks and deep learning.

Frontiers in bioscience (Landmark edition)
BACKGROUND: In the current COVID-19 pandemic, with an absence of approved drugs and widely accessible vaccines, repurposing existing drugs is vital to quickly developing a treatment for the disease.

Predicting Visual Improvement After Macular Hole Surgery: A Combined Model Using Deep Learning and Clinical Features.

Translational vision science & technology
PURPOSE: The purpose of this study was to assess the feasibility of deep learning (DL) methods to enhance the prediction of visual acuity (VA) improvement after macular hole (MH) surgery from a combined model using DL on high-definition optical coher...

Automated prediction of the Thoracolumbar Injury Classification and Severity Score from CT using a novel deep learning algorithm.

Neurosurgical focus
OBJECTIVE: Damage to the thoracolumbar spine can confer significant morbidity and mortality. The Thoracolumbar Injury Classification and Severity Score (TLICS) is used to categorize injuries and determine patients at risk of spinal instability for wh...

Deep learning adapted acceleration for limited-view photoacoustic image reconstruction.

Optics letters
The limited-view issue can cause a low-quality image in photoacoustic (PA) computed tomography due to the limitation of geometric condition. The model-based method is used to resolve this problem, which contains different regularization. To adapt fas...

Predicting the eigenstructures of metamaterials with QR-code meta-atoms by deep learning.

Optics letters
Deep neural networks (DNNs) facilitate the reverse design of metamaterial perfect absorbers (MPAs), usually by predicting the MPA structure from the input absorptivity. However, this suffers from the difficulty that the spectrum that actually exists ...

Deep-learning-based 3D object salient detection via light-field integral imaging.

Optics letters
This Letter proposes an effective light-field 3D saliency object detection (SOD) method, which is inspired by the idea that the spatial and angular information inherent in a light-field implicitly contains the geometry and reflection characteristics ...

Retinal photograph-based deep learning predicts biological age, and stratifies morbidity and mortality risk.

Age and ageing
BACKGROUND: ageing is an important risk factor for a variety of human pathologies. Biological age (BA) may better capture ageing-related physiological changes compared with chronological age (CA).

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study.

The Lancet. Digital health
BACKGROUND: Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of p...