AIMC Topic: Neural Networks, Computer

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Detecting vulnerable plaque with vulnerability index based on convolutional neural networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 19, 2020
Plaque rupture and subsequent thrombosis are major processes of acute cardiovascular events. The Vulnerability Index is a very important indicator of whether a plaque is ruptured, and these easily ruptured or fragile plaques can be detected early. Th...
Humans Neural Networks, Computer Plaque, Atherosclerotic Rupture Risk Assessment Coronary Artery Disease Endosonography
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GAN and dual-input two-compartment model-based training of a neural network for robust quantification of contrast uptake rate in gadoxetic acid-enhanced MRI.

Medical physics Feb 19, 2020
PURPOSE: Gadoxetic acid uptake rate (k ) obtained from dynamic, contrast-enhanced (DCE) magnetic resonance imaging (MRI) is a promising measure of regional liver function. Clinical exams are typically poorly temporally characterized, as seen in a low...
Biological Transport Gadolinium DTPA Neural Networks, Computer Image Processing, Computer-Assisted Contrast Media Magnetic Resonance Imaging Least-Squares Analysis
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fNIRS-GANs: data augmentation using generative adversarial networks for classifying motor tasks from functional near-infrared spectroscopy.

Journal of neural engineering Feb 19, 2020
OBJECTIVE: Functional near-infrared spectroscopy (fNIRS) is expected to be applied to brain-computer interface (BCI) technologies. Since lengthy fNIRS measurements are uncomfortable for participants, it is difficult to obtain enough data to train cla...
Support Vector Machine Psychomotor Performance Movement Humans Brain-Computer Interfaces Adult Neural Networks, Computer Motor Cortex Male Female Spectroscopy, Near-Infrared Young Adult
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Convolutional and recurrent neural network for human activity recognition: Application on American sign language.

PloS one Feb 19, 2020
Human activity recognition is an important and difficult topic to study because of the important variability between tasks repeated several times by a subject and between subjects. This work is motivated by providing time-series signal classification...
Biomechanical Phenomena Male Humans Deep Learning Neural Networks, Computer Machine Learning Sign Language Algorithms Gestures Hand Movement
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Multi-Contrast Super-Resolution MRI Through a Progressive Network.

IEEE transactions on medical imaging Feb 18, 2020
Magnetic resonance imaging (MRI) is widely used for screening, diagnosis, image-guided therapy, and scientific research. A significant advantage of MRI over other imaging modalities such as computed tomography (CT) and nuclear imaging is that it clea...
Tomography, X-Ray Computed Magnetic Resonance Imaging Signal-To-Noise Ratio Neural Networks, Computer
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Numerosity discrimination in deep neural networks: Initial competence, developmental refinement and experience statistics.

Developmental science Feb 18, 2020
Both humans and non-human animals exhibit sensitivity to the approximate number of items in a visual array, as indexed by their performance in numerosity discrimination tasks, and even neonates can detect changes in numerosity. These findings are oft...
Humans Neural Networks, Computer Algorithms Male Deep Learning Child Computer Simulation Female Animals Numerical Analysis, Computer-Assisted Personality Inventory Visual Perception Environment Biological Evolution Cognition Judgment
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Development of AOP relevant to microplastics based on toxicity mechanisms of chemical additives using ToxCast™ and deep learning models combined approach.

Environment international Feb 18, 2020
Various additives are used in plastic products to improve the properties and the durability of the plastics. Their possible elution from the plastics when plastics are fragmented into micro- and nano-size in the environment is suspected to one of the...
Microplastics Neural Networks, Computer Animals Risk Assessment Deep Learning Humans Water Pollutants, Chemical Environmental Pollution
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Feature Extraction of Surface Electromyography Based on Improved Small-World Leaky Echo State Network.

Neural computation Feb 18, 2020
Surface electromyography (sEMG) is an electrophysiological reflection of skeletal muscle contractile activity that can directly reflect neuromuscular activity. It has been a matter of research to investigate feature extraction methods of sEMG signals...
Electromyography Neural Networks, Computer Algorithms Muscle, Skeletal Humans
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Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture.

Biomedical physics & engineering express Feb 18, 2020
BACKGROUND: Magnetic resonance cine imaging is the accepted standard for cardiac functional assessment. Left ventricular (LV) segmentation plays a key role in volumetric functional quantification of the heart. Conventional manual analysis is time-con...
Heart Diseases Observer Variation Automation Magnetic Resonance Imaging, Cine Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Heart Ventricles Ventricular Function, Left
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Microbial Decolorization of Triazo Dye, Direct Blue 71: An Optimization Approach Using Response Surface Methodology (RSM) and Artificial Neural Network (ANN).

BioMed research international Feb 18, 2020
The release of wastewater from textile dyeing industrial sectors is a huge concern with regard to pollution as the treatment of these waters is truly a challenging process. Hence, this study investigates the triazo bond Direct Blue 71 (DB71) dye deco...
Carbon Biodegradation, Environmental Neural Networks, Computer Water Decolorization Nitrogen Bacteria Azo Compounds Hydrogen-Ion Concentration Metagenomics
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