AI Medical Compendium Journal:
Applied optics

Showing 51 to 60 of 60 articles

Intelligent-assistant system for scleral spur location.

Applied optics
A system based on the use of two artificial neural networks (ANNs) to determine the location of the scleral spur of the human eye in ocular images generated by an ultrasound biomicroscopy is presented in this paper. The two ANNs establish a relations...

Convolutional neural network-based approach to estimate bulk optical properties in diffuse optical tomography.

Applied optics
Deep learning has been actively investigated for various applications such as image classification, computer vision, and regression tasks, and it has shown state-of-the-art performance. In diffuse optical tomography (DOT), the accurate estimation of ...

Volumetric analysis of breast cancer tissues using machine learning and swept-source optical coherence tomography.

Applied optics
In breast cancer, 20%-30% of cases require a second surgery because of incomplete excision of malignant tissues. Therefore, to avoid the risk of recurrence, accurate detection of the cancer margin by the clinician or surgeons needs some assistance. I...

Low coherence quantitative phase microscopy with machine learning model and Raman spectroscopy for the study of breast cancer cells and their classification.

Applied optics
Early-stage detection of breast cancer is the primary requirement in modern healthcare as it is the most common cancer among women worldwide. Histopathology is the most widely preferred method for the diagnosis of breast cancer, but it requires long ...

Deep learning enhancement of infrared face images using generative adversarial networks.

Applied optics
This work presents a deep learning framework based on the use of deep convolutional generative adversarial networks (DCGAN) for infrared face image super-resolution. We use DCGAN for upscaling the images by a factor of 4×4, starting at a size of 16×1...

Hybrid gray wolf optimizer-artificial neural network classification approach for magnetic resonance brain images.

Applied optics
Automated and accurate classification of magnetic resonance images (MRIs) of the brain has great importance for medical analysis and interpretation. This paper presents a hybrid optimized classification method to classify the brain tumor by classifyi...

Detection of citrus canker and Huanglongbing using fluorescence imaging spectroscopy and support vector machine technique.

Applied optics
Citrus canker and Huanglongbing (HLB) are citrus diseases that represent a serious threat to the citrus production worldwide and may cause large economic losses. In this work, we combined fluorescence imaging spectroscopy (FIS) and a machine learning...

Fast particle characterization using digital holography and neural networks.

Applied optics
We propose using a neural network approach in conjunction with digital holographic microscopy in order to rapidly determine relevant parameters such as the core and shell diameter of coated, non-absorbing spheres. We do so without requiring a time-co...

Analysis of buried interfaces in multilayer mirrors using grazing incidence extreme ultraviolet reflectometry near resonance edges.

Applied optics
Accurate measurements of optical properties of multilayer (ML) mirrors and chemical compositions of interdiffusion layers are particularly challenging to date. In this work, an innovative and nondestructive experimental characterization method for mu...

Aspherical lens design using hybrid neural-genetic algorithm of contact lenses.

Applied optics
The design of complex contact lenses involves numerous uncertain variables. How to help an optical designer to first design the optimal contact lens to reduce discomfort when wearing a pair of glasses is an essential design concern. This study examin...