AIMC Topic: Spinal Cord

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Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.

NeuroImage Oct 6, 2018
The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and long...
Humans Neural Networks, Computer Reproducibility of Results Pattern Recognition, Automated Multiple Sclerosis Spinal Cord Observer Variation Sensitivity and Specificity Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Automatic spinal cord localization, robust to MRI contrasts using global curve optimization.

Medical image analysis Dec 6, 2017
During the last two decades, MRI has been increasingly used for providing valuable quantitative information about spinal cord morphometry, such as quantification of the spinal cord atrophy in various diseases. However, despite the significant improve...
Reproducibility of Results Humans Magnetic Resonance Imaging Sensitivity and Specificity Machine Learning Spinal Cord Algorithms Image Processing, Computer-Assisted
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Artificial intelligence in neurodegenerative disease research: use of IBM Watson to identify additional RNA-binding proteins altered in amyotrophic lateral sclerosis.

Acta neuropathologica Nov 13, 2017
Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease with no effective treatments. Numerous RNA-binding proteins (RBPs) have been shown to be altered in ALS, with mutations in 11 RBPs causing familial forms of the disease, a...
Gene Expression Amyotrophic Lateral Sclerosis Cerebellum Retrospective Studies Computational Biology RNA-Binding Proteins Scholarly Communication Data Mining Spinal Cord Protein Aggregation, Pathological Humans Artificial Intelligence
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An introduction and overview of machine learning in neurosurgical care.

Acta neurochirurgica Nov 13, 2017
BACKGROUND: Machine learning (ML) is a branch of artificial intelligence that allows computers to learn from large complex datasets without being explicitly programmed. Although ML is already widely manifest in our daily lives in various forms, the c...
Prognosis Decision Making Neurosurgical Procedures Spinal Cord Humans Machine Learning Brain
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Robot-Applied Resistance Augments the Effects of Body Weight-Supported Treadmill Training on Stepping and Synaptic Plasticity in a Rodent Model of Spinal Cord Injury.

Neurorehabilitation and neural repair Jul 25, 2017
BACKGROUND: The application of resistive forces has been used during body weight-supported treadmill training (BWSTT) to improve walking function after spinal cord injury (SCI). Whether this form of training actually augments the effects of BWSTT is ...
Spinal Cord Injuries Oleanolic Acid Recovery of Function Motor Activity Robotics Neuronal Plasticity Hindlimb Exercise Therapy Rats, Sprague-Dawley Saponins Synaptophysin Disease Models, Animal Spinal Cord Female Animals
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An Intelligent Decision System for Intraoperative Somatosensory Evoked Potential Monitoring.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 23, 2015
Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal ...
Support Vector Machine Least-Squares Analysis Spinal Cord False Positive Reactions Spinal Cord Injuries Decision Making, Computer-Assisted Algorithms Computer Systems Intraoperative Neurophysiological Monitoring Humans Artificial Intelligence Evoked Potentials, Somatosensory
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PANDA-T1ρ: Integrating principal component analysis and dictionary learning for fast T1ρ mapping.

Magnetic resonance in medicine Feb 14, 2014
PURPOSE: Long scanning time greatly hinders the widespread application of spin-lattice relaxation in rotating frame (T1ρ) in clinics. In this study, a novel method is proposed to reconstruct the T1ρ-weighted images from undersampled k-space data and ...
Subtraction Technique Magnetic Resonance Imaging Pattern Recognition, Automated Models, Statistical Humans Image Enhancement Principal Component Analysis Systems Integration Machine Learning Computer Simulation Algorithms Reproducibility of Results Data Interpretation, Statistical Brain Sensitivity and Specificity Image Interpretation, Computer-Assisted Spinal Cord
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Spinal Cord Image Denoising Using Dncnn Algorithm.

Current medical imaging Jan 1, 2025
BACKGROUND: Spinal image denoising plays a vital role in the accurate diagnosis of disc herniation (DH).
Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Spinal Cord Intervertebral Disc Displacement Humans Neural Networks, Computer Algorithms
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A Multi-branch Attention-based Deep Learning Method for ALS Identification with sMRI Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
The structural Magnetic resonance imaging (sMRI) of spinal cord plays a significant role in the clinical diagnosis of Amyotrophic Lateral Sclerosis (ALS). But due to small cross-sectional area in the axial plane and long sagittal/coronal expansion of...
Magnetic Resonance Imaging Humans Amyotrophic Lateral Sclerosis Spinal Cord Algorithms Deep Learning Image Processing, Computer-Assisted
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Scratching the Surface of Clinical Deterioration With Deep Learning.

Critical care medicine Aug 1, 2021
Humans Deep Learning Spinal Cord Clinical Deterioration
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