AIMC Journal:
Computer methods and programs in biomedicine

Showing 471 to 480 of 844 articles

Deep learning for registration of region of interest in consecutive wireless capsule endoscopy frames.

Computer methods and programs in biomedicine May 25, 2021
BACKGROUND AND OBJECTIVE: Functional gastrointestinal disorders (FGIDs) are reported as worldwide gastrointestinal (GI) diseases. GI motility assessment can assist the diagnosis of patients with intestine motility dysfunction. Wireless capsule endosc...
Humans Deep Learning Capsule Endoscopy
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Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression.

Computer methods and programs in biomedicine May 18, 2021
BACKGROUND AND OBJECTIVES: Research in Multiple Sclerosis (MS) has recently focused on extracting knowledge from real-world clinical data sources. This type of data is more abundant than data produced during clinical trials and potentially more infor...
Humans Neural Networks, Computer Machine Learning Multiple Sclerosis
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Esophageal cancer detection based on classification of gastrointestinal CT images using improved Faster RCNN.

Computer methods and programs in biomedicine May 16, 2021
PURPOSE: Esophageal cancer is a common malignant tumor in life, which seriously affects human health. In order to reduce the work intensity of doctors and improve detection accuracy, we proposed esophageal cancer detection using deep learning. The ch...
Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed Esophageal Neoplasms
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Convolutional neural network analysis of recurrence plots for high resolution melting classification.

Computer methods and programs in biomedicine May 5, 2021
BACKGROUND AND OBJECTIVE: High resolution melting (HRM) analysis is a rapid and correct method for identification of species, such as, microorganism, bacteria, yeast, virus, etc. HRM data are produced using real-time polymerase chain reaction (PCR) a...
Neural Networks, Computer Support Vector Machine Yeasts
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Multiscale attention guided U-Net architecture for cardiac segmentation in short-axis MRI images.

Computer methods and programs in biomedicine May 4, 2021
BACKGROUND AND OBJECTIVE: Automatic cardiac segmentation plays an utmost role in the diagnosis and quantification of cardiovascular diseases.
Neural Networks, Computer Image Processing, Computer-Assisted Magnetic Resonance Imaging Heart Heart Ventricles Magnetic Resonance Imaging, Cine
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Texture analysis based on U-Net neural network for intracranial hemorrhage identification predicts early enlargement.

Computer methods and programs in biomedicine May 3, 2021
BACKGROUND AND OBJECTIVE: Early hemorrhage enlargement in hypertensive cerebral hemorrhage indicates a poor prognosis. This study aims to predict the early enlargement of cerebral hemorrhage through the intelligent texture analysis of cerebral hemorr...
Humans Neural Networks, Computer Brain Intracranial Hemorrhages
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Chest x-ray automated triage: A semiologic approach designed for clinical implementation, exploiting different types of labels through a combination of four Deep Learning architectures.

Computer methods and programs in biomedicine May 2, 2021
BACKGROUND AND OBJECTIVES: The multiple chest x-ray datasets released in the last years have ground-truth labels intended for different computer vision tasks, suggesting that performance in automated chest x-ray interpretation might improve by using ...
Retrospective Studies Deep Learning Triage Radiography X-Rays
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A deep learning approach for 2D ultrasound and 3D CT/MR image registration in liver tumor ablation.

Computer methods and programs in biomedicine Apr 25, 2021
BACKGROUND AND OBJECTIVE: Liver tumor ablation is often guided by ultrasound (US). Due to poor image quality, intraoperative US is fused with preoperative computed tomography or magnetic tomography (CT/MR) images to provide visual guidance. As of tod...
Humans Tomography, X-Ray Computed Deep Learning Ultrasonography Liver Neoplasms Imaging, Three-Dimensional Image Processing, Computer-Assisted
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An integrated deep learning model for motor intention recognition of multi-class EEG Signals in upper limb amputees.

Computer methods and programs in biomedicine Apr 21, 2021
BACKGROUND AND OBJECTIVE: Recognition of motor intention based on electroencephalogram (EEG) signals has attracted considerable research interest in the field of pattern recognition due to its notable application of non-muscular communication and con...
Humans Deep Learning Electroencephalography Amputees Intention Brain-Computer Interfaces Upper Extremity
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Estimation of tumor parameters using neural networks for inverse bioheat problem.

Computer methods and programs in biomedicine Apr 9, 2021
BACKGROUND AND OBJECTIVE: Some types of cancer cause rapid cell growth, while others cause cells to grow and divide at a slower rate. Certain forms of cancer result in visible growths called tumors. This work proposes an inverse estimation of the siz...
Humans Neural Networks, Computer Computer Simulation Breast Neoplasms Breast
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