AIMC Topic: Neural Networks, Computer

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Removal of computed tomography ring artifacts via radial basis function artificial neural networks.

Physics in medicine and biology
Ring artifacts in computed tomography (CT) images are caused by the undesirable response of detector pixels, which leads to the degradation of CT images. Accordingly, it affects the image interpretation, post-processing, and quantitative analysis. In...

CNN-based PET sinogram repair to mitigate defective block detectors.

Physics in medicine and biology
Positron emission tomography (PET) scanners continue to increase sensitivity and axial coverage by adding an ever expanding array of block detectors. As they age, one or more block detectors may lose sensitivity due to a malfunction or component fail...

Reconstruction error based deep neural networks for coronary heart disease risk prediction.

PloS one
Coronary heart disease (CHD) is one of the leading causes of death worldwide; if suffering from CHD and being in its end-stage, the most advanced treatments are required, such as heart surgery and heart transplant. Moreover, it is not easy to diagnos...

Reaction-diffusion memory unit: Modeling of sensitization, habituation and dishabituation in the brain.

PloS one
We propose a novel approach to investigate the effects of sensitization, habituation and dishabituation in the brain using the analysis of the reaction-diffusion memory unit (RDMU). This unit consists of Morris-Lecar-type sensory, motor, interneuron ...

Skin lesion segmentation using high-resolution convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Skin lesion segmentation is an important but challenging task in computer-aided diagnosis of dermoscopy images. Many segmentation methods based on convolutional neural networks often fail to extract accurate lesion boundarie...

Dilated Skip Convolution for Facial Landmark Detection.

Sensors (Basel, Switzerland)
Facial landmark detection has gained enormous interest for face-related applications due to its success in facial analysis tasks such as facial recognition, cartoon generation, face tracking and facial expression analysis. Many studies have been prop...

Afann: bias adjustment for alignment-free sequence comparison based on sequencing data using neural network regression.

Genome biology
Alignment-free methods, more time and memory efficient than alignment-based methods, have been widely used for comparing genome sequences or raw sequencing samples without assembly. However, in this study, we show that alignment-free dissimilarity ca...

ImageDataExtractor: A Tool To Extract and Quantify Data from Microscopy Images.

Journal of chemical information and modeling
The rise of data science is leading to new paradigms in data-driven materials discovery. This carries an essential notion that large data sources containing chemical structure and property information can be mined in a fashion that detects and exploi...

Evolving multilayer perceptron, and factorial design for modelling and optimization of dye decomposition by bio-synthetized nano CdS-diatomite composite.

Environmental research
Design of experiment and hybrid genetic algorithm optimized multilayer perceptron (GA-MLP) artificial neural network have been employed to model and predict dye decomposition capacity of the biologically synthesized nano CdS diatomite composite. Impa...

Lower Body Kinematics Monitoring in Running Using Fabric-Based Wearable Sensors and Deep Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Continuous kinematic monitoring of runners is crucial to inform runners of inappropriate running habits. Motion capture systems are the gold standard for gait analysis, but they are spatially limited to laboratories. Recently, wearable sensors have g...