AIMC Topic: Magnetic Resonance Imaging

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Deep Learning-Based Neuromelanin MRI Changes of Isolated REM Sleep Behavior Disorder.

Movement disorders : official journal of the Movement Disorder Society Feb 1, 2022
BACKGROUND: Isolated REM sleep behavior disorder (iRBD) is considered a prodromal stage of parkinsonism. Neurodegenerative changes in the substantia nigra pars compacta (SNc) in parkinsonism can be detected using neuromelanin-sensitive MRI.
Humans Deep Learning Substantia Nigra Melanins REM Sleep Behavior Disorder Magnetic Resonance Imaging Parkinson Disease Parkinsonian Disorders
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A Deep Learning Approach to Predicting Disease Progression in Multiple Sclerosis Using Magnetic Resonance Imaging.

Investigative radiology Jan 31, 2022
OBJECTIVES: Magnetic resonance imaging (MRI) is an important tool for diagnosis and monitoring of disease course in multiple sclerosis (MS). However, its prognostic value for predicting disease worsening is still being debated. The aim of this study ...
Humans Deep Learning Artificial Intelligence Magnetic Resonance Imaging Disease Progression Multiple Sclerosis
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Ultrafast water-fat separation using deep learning-based single-shot MRI.

Magnetic resonance in medicine Jan 31, 2022
PURPOSE: To present a deep learning-based reconstruction method for spatiotemporally encoded single-shot MRI to simultaneously obtain water and fat images.
Algorithms Animals Deep Learning Rats Magnetic Resonance Imaging Water Artifacts Image Processing, Computer-Assisted
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Deep learning-based artificial intelligence for prostate cancer detection at biparametric MRI.

Abdominal radiology (New York) Jan 31, 2022
PURPOSE: To present fully automated DL-based prostate cancer detection system for prostate MRI.
Magnetic Resonance Imaging Prostatic Neoplasms Prostate Artificial Intelligence Male Deep Learning Humans
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Effect of head motion-induced artefacts on the reliability of deep learning-based whole-brain segmentation.

Scientific reports Jan 31, 2022
Due to their robustness and speed, recently developed deep learning-based methods have the potential to provide a faster and hence more scalable alternative to more conventional neuroimaging analysis pipelines in terms of whole-brain segmentation bas...
Young Adult Adult Head Movements Male Female Humans Reproducibility of Results Brain Artifacts Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Head Neuroimaging
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Interpretable Model Based on Pyramid Scene Parsing Features for Brain Tumor MRI Image Segmentation.

Computational and mathematical methods in medicine Jan 31, 2022
Due to the black box model nature of convolutional neural networks, computer-aided diagnosis methods based on depth learning are usually poorly interpretable. Therefore, the diagnosis results obtained by these unexplained methods are difficult to gai...
Diagnosis, Computer-Assisted Algorithms Neuroimaging Humans Computational Biology Databases, Factual Neural Networks, Computer Magnetic Resonance Imaging Brain Neoplasms
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Brain tumor segmentation in MRI images using nonparametric localization and enhancement methods with U-net.

International journal of computer assisted radiology and surgery Jan 29, 2022
PURPOSE: Segmentation is one of the critical steps in analyzing medical images since it provides meaningful information for the diagnosis, monitoring, and treatment of brain tumors. In recent years, several artificial intelligence-based systems have ...
Magnetic Resonance Imaging Artificial Intelligence Brain Neoplasms Image Processing, Computer-Assisted Humans Neural Networks, Computer
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A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society Jan 28, 2022
PURPOSE: To improve the performance of less experienced clinicians in the diagnosis of benign and malignant spinal fracture on MRI, we applied the ResNet50 algorithm to develop a decision support system.
Spinal Neoplasms Spinal Fractures Humans Retrospective Studies Deep Learning Magnetic Resonance Imaging Diagnosis, Differential
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Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

Circulation. Arrhythmia and electrophysiology Jan 28, 2022
BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while ...
Humans Machine Learning Risk Factors Magnetic Resonance Imaging Action Potentials Electrocardiography, Ambulatory Risk Assessment Time Factors Treatment Outcome Atrial Function, Left Models, Cardiovascular Patient-Specific Modeling Atrial Remodeling Heart Rate Catheter Ablation Recurrence Fibrosis Atrial Fibrillation
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Multi-label classification of pelvic organ prolapse using stress magnetic resonance imaging with deep learning.

International urogynecology journal Jan 27, 2022
INTRODUCTION AND HYPOTHESIS: We aimed to develop a deep learning-based multi-label classification model to simultaneously diagnose three types of pelvic organ prolapse using stress magnetic resonance imaging (MRI).
Pelvic Organ Prolapse Magnetic Resonance Imaging Pelvic Floor Humans Deep Learning
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