AIMC Topic: Signal-To-Noise Ratio

Clear Filters Showing 941 to 950 of 953 articles

Teaching learning based optimization-functional link artificial neural network filter for mixed noise reduction from magnetic resonance image.

Bio-medical materials and engineering
BACKGROUND: The clinical magnetic resonance imaging (MRI) images may get corrupted due to the presence of the mixture of different types of noises such as Rician, Gaussian, impulse, etc. Most of the available filtering algorithms are noise specific, ...

Learning-based 3T brain MRI segmentation with guidance from 7T MRI labeling.

Medical physics
PURPOSE: Segmentation of brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is crucial for brain structural measurement and disease diagnosis. Learning-based segmentation methods depend largel...

Learning-based 3T brain MRI segmentation with guidance from 7T MRI labeling.

Medical physics
PURPOSE: Segmentation of brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is crucial for brain structural measurement and disease diagnosis. Learning-based segmentation methods depend largel...

Design and validation of an MR-conditional robot for transcranial focused ultrasound surgery in infants.

Medical physics
PURPOSE: Current treatment of intraventricular hemorrhage (IVH) involves cerebral shunt placement or an invasive brain surgery. Magnetic resonance-guided focused ultrasound (MRgFUS) applied to the brains of pediatric patients presents an opportunity ...

Recursive feature elimination for biomarker discovery in resting-state functional connectivity.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Biomarker discovery involves finding correlations between features and clinical symptoms to aid clinical decision. This task is especially difficult in resting state functional magnetic resonance imaging (rs-fMRI) data due to low SNR, high-dimensiona...

Improving quality and intelligibility of speech using single microphone for the broadband fMRI noise at low SNR.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Functional Magnetic Resonance Imaging (fMRI) is used in many diagnostic procedures for neurological related disorders. Strong broadband acoustic noise generated during fMRI scan interferes with the speech communication between the physician and the p...

Genetic algorithms for dipole location of fetal magnetocardiography.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this paper, we explore the use of Maximum Likelihood (ML) method with Genetic Algorithms (GA) as global optimization procedure for source reconstruction in fetal magnetocardiography (fMCG) data. A multiple equivalent current dipole (ECD) model was...

Electrocardiogram signal denoising based on a new improved wavelet thresholding.

The Review of scientific instruments
Good quality electrocardiogram (ECG) is utilized by physicians for the interpretation and identification of physiological and pathological phenomena. In general, ECG signals may mix various noises such as baseline wander, power line interference, and...

Combined fuzzy logic and random walker algorithm for PET image tumor delineation.

Nuclear medicine communications
PURPOSE: The random walk (RW) technique serves as a powerful tool for PET tumor delineation, which typically involves significant noise and/or blurring. One challenging step is hard decision-making in pixel labeling. Fuzzy logic techniques have achie...

Intrinsic excitability state of local neuronal population modulates signal propagation in feed-forward neural networks.

Chaos (Woodbury, N.Y.)
Reliable signal propagation across distributed brain areas is an essential requirement for cognitive function, and it has been investigated extensively in computational studies where feed-forward network (FFN) is taken as a generic model. But it is s...