AIMC Topic: Convolutional Neural Networks

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A review of convolutional neural network based methods for medical image classification.

Computers in biology and medicine Dec 3, 2024
This study systematically reviews CNN-based medical image classification methods. We surveyed 149 of the latest and most important papers published to date and conducted an in-depth analysis of the methods used therein. Based on the selected literatu...
Humans Image Processing, Computer-Assisted Diagnostic Imaging Image Interpretation, Computer-Assisted Neural Networks, Computer Deep Learning Convolutional Neural Networks
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Identification of structural stability and fragility of mouse liver glycogen via label-free Raman spectroscopy coupled with convolutional neural network algorithm.

International journal of biological macromolecules Dec 3, 2024
Glycogen structure is closely associated with its physiological functions. Previous studies confirmed that liver glycogen structure had two dominant states: mainly stable during the day and largely fragile at night. However, the diurnal change of gly...
Neural Networks, Computer Algorithms Animals Liver Glycogen Convolutional Neural Networks Mice Spectrum Analysis, Raman Liver Glycogen
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Intra- and inter-channel deep convolutional neural network with dynamic label smoothing for multichannel biosignal analysis.

Neural networks : the official journal of the International Neural Network Society Dec 2, 2024
Efficient processing of multichannel biosignals has significant application values in the fields of healthcare and human-machine interaction. Although previous research has achieved high recognition performance with deep convolutional neural networks...
Neural Networks, Computer Machine Learning Deep Learning Humans Convolutional Neural Networks Electroencephalography Signal Processing, Computer-Assisted
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Algal classification and Chlorophyll-a concentration determination using convolutional neural networks and three-dimensional fluorescence data matrices.

Environmental research Dec 2, 2024
In recent years, the frequency of harmful algal blooms has increased, leading to the release of large quantities of toxins and compounds that cause unpleasant odors and tastes, significantly compromising drinking water quality. Chlorophyll-a (Chl-a) ...
Chlorophyll A Chlorella Neural Networks, Computer Fluorescence Microcystis Chlorophyll Convolutional Neural Networks Environmental Monitoring Harmful Algal Bloom
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Estimating Ground Reaction Forces from Gait Kinematics in Cerebral Palsy: A Convolutional Neural Network Approach.

Annals of biomedical engineering Nov 30, 2024
PURPOSE: While gait analysis is essential for assessing neuromotor disorders like cerebral palsy (CP), capturing accurate ground reaction force (GRF) measurements during natural walking presents challenges, particularly due to variations in gait patt...
Adult Biomechanical Phenomena Male Child Humans Neural Networks, Computer Gait Female Cerebral Palsy Convolutional Neural Networks Adolescent
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Facial expression analysis using convolutional neural network for drug-naive and chronic schizophrenia.

Journal of psychiatric research Nov 29, 2024
OBJECTIVE: Facial images have been shown to convey mental conditions as clinical symptoms. This study aimed to use facial images to detect patients with drug-naive schizophrenia (DN-SCZ) or chronic schizophrenia (C-SCZ) from healthy controls (HCs), a...
Male Facial Expression Convolutional Neural Networks Female Middle Aged Chronic Disease Young Adult Facial Recognition Schizophrenia Adult Humans Neural Networks, Computer
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Incorporating label uncertainty during the training of convolutional neural networks improves performance for the discrimination between certain and inconclusive cases in dopamine transporter SPECT.

European journal of nuclear medicine and molecular imaging Nov 27, 2024
PURPOSE: Deep convolutional neural networks (CNN) hold promise for assisting the interpretation of dopamine transporter (DAT)-SPECT. For improved communication of uncertainty to the user it is crucial to reliably discriminate certain from inconclusiv...
Humans Neural Networks, Computer Retrospective Studies Convolutional Neural Networks Image Processing, Computer-Assisted Tomography, Emission-Computed, Single-Photon Uncertainty Dopamine Plasma Membrane Transport Proteins
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BEAS-Net: A Shape-Prior-Based Deep Convolutional Neural Network for Robust Left Ventricular Segmentation in 2-D Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 27, 2024
Left ventricle (LV) segmentation of 2-D echocardiography images is an essential step in the analysis of cardiac morphology and function and-more generally-diagnosis of cardiovascular diseases (CVD). Several deep learning (DL) algorithms have recently...
Heart Ventricles Algorithms Echocardiography Deep Learning Convolutional Neural Networks Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Binarized Simplicial Convolutional Neural Networks.

Neural networks : the official journal of the International Neural Network Society Nov 23, 2024
Graph Neural Networks have the limitation of processing features solely on graph nodes, neglecting data on high-dimensional structures such as edges and triangles. Simplicial Convolutional Neural Networks (SCNN) represent high-order structures using ...
Neural Networks, Computer Algorithms Convolutional Neural Networks
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Convolutional neural network classification of ultrasound parametric images based on echo-envelope statistics for the quantitative diagnosis of liver steatosis.

Journal of medical ultrasonics (2001) Nov 23, 2024
PURPOSE: Early detection and quantitative evaluation of liver steatosis are crucial. Therefore, this study investigated a method for classifying ultrasound images to fatty liver grades based on echo-envelope statistics (ES) and convolutional neural n...
Adult Image Interpretation, Computer-Assisted Male Middle Aged Magnetic Resonance Imaging Humans Convolutional Neural Networks Liver Neural Networks, Computer Ultrasonography Female Fatty Liver
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