AIMC Topic: Artifacts

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Near-Bayesian Support Vector Machines for imbalanced data classification with equal or unequal misclassification costs.

Neural networks : the official journal of the International Neural Network Society Jul 8, 2015
Support Vector Machines (SVMs) form a family of popular classifier algorithms originally developed to solve two-class classification problems. However, SVMs are likely to perform poorly in situations with data imbalance between the classes, particula...
Datasets as Topic Support Vector Machine Data Interpretation, Statistical Bayes Theorem Artifacts Algorithms
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Understanding safety-critical interactions with a home medical device through Distributed Cognition.

Journal of biomedical informatics Jun 6, 2015
As healthcare shifts from the hospital to the home, it is becoming increasingly important to understand how patients interact with home medical devices, to inform the safe and patient-friendly design of these devices. Distributed Cognition (DCog) has...
Equipment and Supplies Artifacts United Kingdom Renal Insufficiency Interior Design and Furnishings Anthropology, Cultural Hemodialysis, Home Renal Dialysis Residence Characteristics Decision Making Data Collection Adult Male Middle Aged Humans Artificial Intelligence Software Algorithms Patient Safety Female Aged
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Echocardiogram enhancement using supervised manifold denoising.

Medical image analysis May 21, 2015
This paper presents data-driven methods for echocardiogram enhancement. Existing denoising algorithms typically rely on a single noise model, and do not generalize to the composite noise sources typically found in real-world echocardiograms. Our meth...
Humans Algorithms Signal-To-Noise Ratio Image Interpretation, Computer-Assisted Artifacts Pattern Recognition, Automated Image Enhancement Reproducibility of Results Sensitivity and Specificity Echocardiography Supervised Machine Learning
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Systematic artifacts in support vector regression-based compound potency prediction revealed by statistical and activity landscape analysis.

PloS one Mar 5, 2015
Support vector machines are a popular machine learning method for many classification tasks in biology and chemistry. In addition, the support vector regression (SVR) variant is widely used for numerical property predictions. In chemoinformatics and ...
Structure-Activity Relationship Drug Evaluation, Preclinical Artifacts Humans Drug Discovery Support Vector Machine
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Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification.

NeuroImage Jan 5, 2015
Signal drift in functional magnetic resonance imaging (fMRI) is an unavoidable artifact that limits classification performance in multi-voxel pattern analysis of fMRI. As conventional methods to reduce signal drift, global demeaning or proportional s...
Multivariate Analysis Brain Young Adult Adult Male Support Vector Machine Magnetic Resonance Imaging Brain Mapping Artifacts Humans
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Decoding objects of basic categories from electroencephalographic signals using wavelet transform and support vector machines.

Brain topography May 17, 2014
Decoding and classification of objects through task-oriented electroencephalographic (EEG) signals are the most crucial goals of recent researches conducted mainly for brain-computer interface applications. In this study we aimed to classify single-t...
Electroencephalography Signal Processing, Computer-Assisted Artifacts Wavelet Analysis Photic Stimulation Pattern Recognition, Visual Adult Male Adolescent Support Vector Machine Brain Female Young Adult Humans
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A multistaged automatic restoration of noisy microscopy cell images.

IEEE journal of biomedical and health informatics Feb 10, 2014
Automated cell segmentation for microscopy cell images has recently become an initial step for further image analysis in cell biology. However, microscopy cell images are easily degraded by noise during the readout procedure via optical-electronic im...
Reproducibility of Results Sensitivity and Specificity Data Interpretation, Statistical Microscopy Artificial Intelligence Algorithms Image Enhancement Signal-To-Noise Ratio Cell Tracking Image Interpretation, Computer-Assisted Artifacts Pattern Recognition, Automated Yeasts
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Artifact-robust Deep Learning-based Segmentation of 3D Phase-contrast MR Angiography: A Novel Data Augmentation Approach.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Dec 25, 2025
This study presents a novel data augmentation approach to improve deep learning (DL)-based segmentation for 3D phase-contrast magnetic resonance angiography (PC-MRA) images affected by pulsation artifacts. Augmentation was achieved by simulating puls...
Humans Algorithms Female Image Processing, Computer-Assisted Contrast Media Artifacts Magnetic Resonance Angiography Adult Male Deep Learning Imaging, Three-Dimensional
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The Impact of Model-based Deep-learning Reconstruction Compared with that of Compressed Sensing-Sensitivity Encoding on the Image Quality and Precision of Cine Cardiac MR in Evaluating Left-ventricular Volume and Strain: A Study on Healthy Volunteers.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Nov 20, 2025
PURPOSE: To evaluate the effect of model-based deep-learning reconstruction (DLR) compared with that of compressed sensing-sensitivity encoding (CS) on cine cardiac magnetic resonance (CMR).
Magnetic Resonance Imaging, Cine Heart Ventricles Healthy Volunteers Artifacts Data Compression Adult Male Ventricular Function, Left Stroke Volume Middle Aged Deep Learning Image Processing, Computer-Assisted Heart Humans Female Reproducibility of Results Young Adult
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Deep Learning Reconstruction for 7T MP2RAGE and SPACE MRI: Improving Image Quality at High Acceleration Factors.

AJNR. American journal of neuroradiology Nov 3, 2025
BACKGROUND AND PURPOSE: Deep learning (DL) reconstruction has been successful in realizing otherwise impracticable acceleration factors and improving image quality in conventional MRI field strengths; however, there has been limited application to ul...
Humans Brain Retrospective Studies Middle Aged Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Female Aged Adult Male Image Interpretation, Computer-Assisted Artifacts Signal-To-Noise Ratio
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