AIMC Topic:
Magnetic Resonance Imaging

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Benchmarking explanation methods for mental state decoding with deep learning models.

NeuroImage Apr 13, 2023
Deep learning (DL) models find increasing application in mental state decoding, where researchers seek to understand the mapping between mental states (e.g., experiencing anger or joy) and brain activity by identifying those spatial and temporal feat...
Brain Deep Learning Magnetic Resonance Imaging Humans Artificial Intelligence Brain Mapping Benchmarking
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Deep learning synthesis of cone-beam computed tomography from zero echo time magnetic resonance imaging.

Scientific reports Apr 13, 2023
Cone-beam computed tomography (CBCT) produces high-resolution of hard tissue even in small voxel size, but the process is associated with radiation exposure and poor soft tissue imaging. Thus, we synthesized a CBCT image from the magnetic resonance i...
Deep Learning Cone-Beam Computed Tomography Magnetic Resonance Imaging Artifacts Image Processing, Computer-Assisted Phantoms, Imaging Humans
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Automated Triage of Screening Breast MRI Examinations in High-Risk Women Using an Ensemble Deep Learning Model.

Investigative radiology Apr 11, 2023
OBJECTIVES: The aim of the study is to develop and evaluate the performance of a deep learning (DL) model to triage breast magnetic resonance imaging (MRI) findings in high-risk patients without missing any cancers.
Magnetic Resonance Imaging Triage Breast Neoplasms Deep Learning Humans Retrospective Studies Female
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CORR Insights®: Can a Deep Learning Algorithm Improve Detection of Occult Scaphoid Fractures in Plain Radiographs? A Clinical Validation Study.

Clinical orthopaedics and related research Apr 11, 2023
Radiography Fractures, Closed Scaphoid Bone Magnetic Resonance Imaging Fractures, Bone Humans Deep Learning
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Interactive Explainable Deep Learning Model Informs Prostate Cancer Diagnosis at MRI.

Radiology Apr 11, 2023
Background Clinically significant prostate cancer (PCa) diagnosis at MRI requires accurate and efficient radiologic interpretation. Although artificial intelligence may assist in this task, lack of transparency has limited clinical translation. Purpo...
Prostatic Neoplasms Prostate Deep Learning Magnetic Resonance Imaging Humans Artificial Intelligence Aged Male Retrospective Studies
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A unique color-coded visualization system with multimodal information fusion and deep learning in a longitudinal study of Alzheimer's disease.

Artificial intelligence in medicine Apr 7, 2023
PURPOSE: Automated diagnosis and prognosis of Alzheimer's Disease remain a challenging problem that machine learning (ML) techniques have attempted to resolve in the last decade. This study introduces a first-of-its-kind color-coded visualization mec...
Longitudinal Studies Magnetic Resonance Imaging Deep Learning Humans Alzheimer Disease Cognitive Dysfunction Disease Progression tau Proteins Amyloid beta-Peptides
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High-resolution imaging of the excised porcine heart at a whole-body 7 T MRI system using an 8Tx/16Rx pTx coil.

Magma (New York, N.Y.) Apr 7, 2023
INTRODUCTION: MRI of excised hearts at ultra-high field strengths ([Formula: see text]≥7 T) can provide high-resolution, high-fidelity ground truth data for biomedical studies, imaging science, and artificial intelligence. In this study, we demonstra...
Artificial Intelligence Magnetic Resonance Imaging Equipment Design Signal-To-Noise Ratio Animals Swine Phantoms, Imaging Diffusion Tensor Imaging
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The Impact of Fatty Infiltration on MRI Segmentation of Lower Limb Muscles in Neuromuscular Diseases: A Comparative Study of Deep Learning Approaches.

Journal of magnetic resonance imaging : JMRI Apr 6, 2023
BACKGROUND: Deep learning methods have been shown to be useful for segmentation of lower limb muscle MRIs of healthy subjects but, have not been sufficiently evaluated on neuromuscular disease (NDM) patients.
Muscles Aged Neuromuscular Diseases Adult Humans Magnetic Resonance Imaging Deep Learning Retrospective Studies Thigh Image Processing, Computer-Assisted Reproducibility of Results Middle Aged
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Editorial for "The Impact of Fatty Infiltration on MRI Segmentation of Lower Limb Muscles in Neuromuscular Diseases: A Comparative Study of Deep Learning Approaches".

Journal of magnetic resonance imaging : JMRI Apr 6, 2023
Humans Lower Extremity Deep Learning Muscles Magnetic Resonance Imaging Neuromuscular Diseases
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Physics-informed deep learning approach to quantification of human brain metabolites from magnetic resonance spectroscopy data.

Computers in biology and medicine Apr 5, 2023
PURPOSE: While the recommended analysis method for magnetic resonance spectroscopy data is linear combination model (LCM) fitting, the supervised deep learning (DL) approach for quantification of MR spectroscopy (MRS) and MR spectroscopic imaging (MR...
Image Processing, Computer-Assisted Neural Networks, Computer Magnetic Resonance Imaging Brain Magnetic Resonance Spectroscopy Humans Deep Learning
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