AIMC Topic:
Magnetic Resonance Imaging

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Deep learning-based affine medical image registration for multimodal minimal-invasive image-guided interventions - A comparative study on generalizability.

Zeitschrift fur medizinische Physik Jun 22, 2023
Multimodal image registration is applied in medical image analysis as it allows the integration of complementary data from multiple imaging modalities. In recent years, various neural network-based approaches for medical image registration have been ...
Liver Tomography, X-Ray Computed Multimodal Imaging Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Neural Networks, Computer
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Increased functional connectivity coupling with supplementary motor area in blepharospasm at rest.

Brain research Jun 22, 2023
OBJECTIVE: To explore the abnormalities of brain function in blepharospasm (BSP) and to illustrate its neural mechanisms by assuming supplementary motor area (SMA) as the entry point.
Humans Adult Male Blepharospasm Magnetic Resonance Imaging Prefrontal Cortex Middle Aged Motor Cortex Connectome Rest Support Vector Machine
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Deep learning-assisted model-based off-resonance correction for non-Cartesian SWI.

Magnetic resonance in medicine Jun 22, 2023
PURPOSE: Patient-induced inhomogeneities in the static magnetic field cause distortions and blurring (off-resonance artifacts) during acquisitions with long readouts such as in SWI. Conventional versatile correction methods based on extended Fourier ...
Magnetic Resonance Imaging Deep Learning Image Processing, Computer-Assisted Algorithms Brain Humans Neural Networks, Computer
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Fetal magnetic resonance imaging artifacts: role of deep learning to improve imaging.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology Jun 22, 2023
Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Deep Learning Artifacts
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Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learning.

European radiology Jun 20, 2023
OBJECTIVES: To use convolutional neural network for fully automated segmentation and radiomics features extraction of hypopharyngeal cancer (HPC) tumor in MRI.
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Reproducibility of Results Hypopharyngeal Neoplasms
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Computerised emergency work-up for mass-like brain MRI lesions: can explainable AI support radiologists?

European radiology Jun 20, 2023
Magnetic Resonance Imaging Multiparametric Magnetic Resonance Imaging Neoplasms Deep Learning Humans Artificial Intelligence Brain
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Functional Alignment-Auxiliary Generative Adversarial Network-Based Visual Stimuli Reconstruction via Multi-Subject fMRI.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 20, 2023
Functional Magnetic Resonance Imaging (fMRI) provides more precise spatial and temporal information to reconstruct stimulus images than other technologies that can be used to measure the human brain's neural responses. The fMRI scans, however, genera...
Image Processing, Computer-Assisted Brain Magnetic Resonance Imaging Reproducibility of Results Humans Neural Networks, Computer
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An automatic interpretable deep learning pipeline for accurate Parkinson's disease diagnosis using quantitative susceptibility mapping and T1-weighted images.

Human brain mapping Jun 19, 2023
Parkinson's disease (PD) diagnosis based on magnetic resonance imaging (MRI) is still challenging clinically. Quantitative susceptibility maps (QSM) can potentially provide underlying pathophysiological information by detecting the iron distribution ...
Parkinson Disease Deep Learning Humans Brain Mapping Globus Pallidus Gray Matter Magnetic Resonance Imaging Caudate Nucleus
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Adapting model-based deep learning to multiple acquisition conditions: Ada-MoDL.

Magnetic resonance in medicine Jun 18, 2023
PURPOSE: The aim of this work is to introduce a single model-based deep network that can provide high-quality reconstructions from undersampled parallel MRI data acquired with multiple sequences, acquisition settings, and field strengths.
Image Processing, Computer-Assisted Neural Networks, Computer Magnetic Resonance Imaging Deep Learning
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An Optimized Deep Learning Model for Predicting Mild Cognitive Impairment Using Structural MRI.

Sensors (Basel, Switzerland) Jun 16, 2023
Early diagnosis of mild cognitive impairment (MCI) with magnetic resonance imaging (MRI) has been shown to positively affect patients' lives. To save time and costs associated with clinical investigation, deep learning approaches have been used widel...
Alzheimer Disease Entorhinal Cortex Cognitive Dysfunction Magnetic Resonance Imaging Humans Deep Learning
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