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Ophthalmic diagnosis using deep learning with fundus images - A critical review.

Artificial intelligence in medicine
An overview of the applications of deep learning for ophthalmic diagnosis using retinal fundus images is presented. We describe various retinal image datasets that can be used for deep learning purposes. Applications of deep learning for segmentation...

Robust and Accurate Hand-Eye Calibration Method Based on Schur Matric Decomposition.

Sensors (Basel, Switzerland)
To improve the accuracy and robustness of hand-eye calibration, a hand-eye calibration method based on Schur matric decomposition is proposed in this paper. The accuracy of these methods strongly depends on the quality of observation data. Therefore,...

Hyper-reflective foci segmentation in SD-OCT retinal images with diabetic retinopathy using deep convolutional neural networks.

Medical physics
PURPOSE: The purpose of this study was to automatically and accurately segment hyper-reflective foci (HRF) in spectral domain optical coherence tomography (SD-OCT) images with diabetic retinopathy (DR) using deep convolutional neural networks.

Predicting gene regulatory interactions based on spatial gene expression data and deep learning.

PLoS computational biology
Reverse engineering of gene regulatory networks (GRNs) is a central task in systems biology. Most of the existing methods for GRN inference rely on gene co-expression analysis or TF-target binding information, where the determination of co-expression...

Development of the Self Optimising Kohonen Index Network (SKiNET) for Raman Spectroscopy Based Detection of Anatomical Eye Tissue.

Scientific reports
Raman spectroscopy shows promise as a tool for timely diagnostics via in-vivo spectroscopy of the eye, for a number of ophthalmic diseases. By measuring the inelastic scattering of light, Raman spectroscopy is able to reveal detailed chemical charact...

Diagnostic Quality Assessment of Ocular Fundus Photographs: Efficacy of Structure-Preserving ScatNet Features.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Various ophthalmic procedures critically depend on high-quality images. For instance, efficiency of teleophthalmology, a framework to bring advanced eye care to remote regions, is determined by the capability of assessing diagnostic quality of ocular...

Extract Features from Periocular Region to Identify the Age Using Machine Learning Algorithms.

Journal of medical systems
Latest studies done on huge data collected from aging features proved that the performance of facial image based age estimation is low and need to be improved. One of the significant biometric traits for human recognition or search is Human age. Age ...

Chip-on-tip endoscope incorporating a soft robotic pneumatic bending microactuator.

Biomedical microdevices
In the ever advancing field of minimally invasive surgery, flexible instruments with local degrees of freedom are needed to navigate through the intricate topologies of the human body. Although cable or concentric tube driven solutions have proven th...

High Intraocular Pressure Detection from Frontal Eye Images: A Machine Learning Based Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents a novel framework to detect the status of intraocular pressure (normal/high) using solely frontal eye image analysis. The framework is based on machine learning approaches to extract six features from frontal eye images. These fea...

Comparison of Machine-Learning Classification Models for Glaucoma Management.

Journal of healthcare engineering
This study develops an objective machine-learning classification model for classifying glaucomatous optic discs and reveals the classificatory criteria to assist in clinical glaucoma management. In this study, 163 glaucoma eyes were labelled with fou...