AIMC Topic: Neural Networks, Computer

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A computer-aided diagnosis system for brain magnetic resonance imaging images using a novel differential feature neural network.

Computers in biology and medicine
To improve the performance of brain tumor diagnosis, numerous automatic brain tumor diagnosis systems that use machine learning technologies have been proposed. However, most current systems ignore the structural symmetry of brain magnetic resonance ...

Real-Time Energy Efficient Hand Pose Estimation: A Case Study.

Sensors (Basel, Switzerland)
The estimation of human hand pose has become the basis for many vital applications where the user depends mainly on the hand pose as a system input. Virtual reality (VR) headset, shadow dexterous hand and in-air signature verification are a few examp...

EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research.

Computational and mathematical methods in medicine
In recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) signal analysis methods, using EEG signals to monitor human health has become a very popular research fi...

Automatic detection of various abnormalities in capsule endoscopy videos by a deep learning-based system: a multicenter study.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: A deep convolutional neural network (CNN) system could be a high-level screening tool for capsule endoscopy (CE) reading but has not been established for targeting various abnormalities. We aimed to develop a CNN-based system and...

Automatic Grading System for Diabetic Retinopathy Diagnosis Using Deep Learning Artificial Intelligence Software.

Current eye research
: To describe the development and validation of an artificial intelligence-based, deep learning algorithm (DeepDR) for the detection of diabetic retinopathy (DR) in retinal fundus photographs. : Five hundred fundus images, which had detailed labellin...

The use of artificial neural network (ANN) for modeling adsorption of sunset yellow onto neodymium modified ordered mesoporous carbon.

Chemosphere
Discharging coloring products in water bodies has degraded water quality irreversibly over the past several decades. Order mesoporous carbon (OMC) was modified by embedding neodymium(III) chloride on the surface of OMC to enhance the adsorptive remov...

Automated detection and classification of shoulder arthroplasty models using deep learning.

Skeletal radiology
OBJECTIVE: To develop and evaluate the performance of deep convolutional neural networks (DCNN) to detect and identify specific total shoulder arthroplasty (TSA) models.

Impulsive synchronization of coupled delayed neural networks with actuator saturation and its application to image encryption.

Neural networks : the official journal of the International Neural Network Society
The actuator of any physical control systems is constrained by amplitude and energy, which causes the control systems to be inevitably affected by actuator saturation. In this paper, impulsive synchronization of coupled delayed neural networks with a...

Learning from irregularly sampled data for endomicroscopy super-resolution: a comparative study of sparse and dense approaches.

International journal of computer assisted radiology and surgery
PURPOSE: Probe-based confocal laser endomicroscopy (pCLE) enables performing an optical biopsy via a probe. pCLE probes consist of multiple optical fibres arranged in a bundle, which taken together generate signals in an irregularly sampled pattern. ...

Deep learning in generating radiology reports: A survey.

Artificial intelligence in medicine
Substantial progress has been made towards implementing automated radiology reporting models based on deep learning (DL). This is due to the introduction of large medical text/image datasets. Generating radiology coherent paragraphs that do more than...