AIMC Topic: Magnetic Resonance Imaging

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A framework for optimal kernel-based manifold embedding of medical image data.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jun 9, 2014
Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, ...
Machine Learning Algorithms Brain Reproducibility of Results Pattern Recognition, Automated Image Enhancement Sensitivity and Specificity Magnetic Resonance Imaging Image Interpretation, Computer-Assisted
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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 ...
Magnetic Resonance Imaging Brain Data Interpretation, Statistical Humans Models, Statistical Machine Learning Image Enhancement Computer Simulation Image Interpretation, Computer-Assisted Algorithms Reproducibility of Results Principal Component Analysis Systems Integration Spinal Cord Sensitivity and Specificity Subtraction Technique Pattern Recognition, Automated
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[Enhancement of radiomics-based machine learning models for predicting efficacy of high-intensity focused ultrasound ablation of uterine fibroids using undersampling methods].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University Jan 20, 2026
OBJECTIVES: To improve the accuracy of machine learning models for preoperative prediction of high-intensity focused ultrasound (HIFU) ablation efficacy for uterine fibroids by correcting class imbalance in small sample datasets using undersampling m...
Humans Machine Learning Magnetic Resonance Imaging Uterine Neoplasms Leiomyoma High-Intensity Focused Ultrasound Ablation Algorithms Female Radiomics Treatment Outcome
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[Research progress on quantitative magnetic susceptibility imaging reconstruction method based on improved U-network model].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2025
Quantitative magnetic susceptibility imaging (QSM) is an imaging method based on magnetic resonance imaging (MRI) phase signal processing and inversion to obtain tissue magnetic susceptibility distribution, which can generate images reflecting the ma...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Algorithms Brain Deep Learning Humans Neural Networks, Computer Machine Learning
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[An unsupervised three-dimensional medical image registration method based on shifted window Transformer and convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2025
Three-dimensional (3D) deformable image registration plays a critical role in 3D medical image processing. This technique aligns images from different time points, modalities, or individuals in 3D space, enabling the comparison and fusion of anatomic...
Humans Neural Networks, Computer Magnetic Resonance Imaging Algorithms Convolutional Neural Networks Imaging, Three-Dimensional Image Processing, Computer-Assisted
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[Detection of neurofibroma combining radiomics and ensemble learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2025
This study proposes an automated neurofibroma detection method for whole-body magnetic resonance imaging (WBMRI) based on radiomics and ensemble learning. A dynamic weighted box fusion mechanism integrating two dimensional (2D) object detection and t...
Humans Machine Learning Algorithms Ensemble Learning Whole Body Imaging Radiomics Neurofibroma Imaging, Three-Dimensional Magnetic Resonance Imaging
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[Localizing target for transcranial electrical stimulation in epilepsy patients combining scalp electroencephalogram and neural computational model].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2025
For patients with MRI-negative drug-resistant epilepsy, noninvasive localization of targets for transcranial electrical stimulation (tES) remains a clinical challenge. This study proposes a novel target localization approach that integrates electroen...
Drug Resistant Epilepsy Electrocorticography Epilepsy Scalp Neural Networks, Computer Transcranial Direct Current Stimulation Brain Computer Simulation Adult Magnetic Resonance Imaging Brain Mapping Humans Electroencephalography
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Robust Radiomic Signatures of Intervertebral Disc Degeneration From MRI.

Spine Dec 15, 2025
STUDY DESIGN: A retrospective analysis.
Lumbar Vertebrae Intervertebral Disc Degeneration Low Back Pain Finland Intervertebral Disc Humans Retrospective Studies Middle Aged Deep Learning Cohort Studies Magnetic Resonance Imaging Female Radiomics Male
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Combined magnetic resonance imaging and serum analysis reveals distinct multiple sclerosis types.

Brain : a journal of neurology Dec 4, 2025
Multiple sclerosis (MS) is a highly heterogeneous disease in its clinical manifestation and progression. Predicting individual disease courses is key for aligning treatments with underlying pathobiology. We developed an unsupervised machine learning ...
Multiple Sclerosis Neurofilament Proteins Multiple Sclerosis, Relapsing-Remitting Multiple Sclerosis, Chronic Progressive Middle Aged Disease Progression Humans Female Cohort Studies Machine Learning Adult Magnetic Resonance Imaging Biomarkers Male Brain
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Deep Learning-Based Prediction of PET Amyloid Status Using MRI.

AJNR. American journal of neuroradiology Dec 4, 2025
BACKGROUND AND PURPOSE: Identifying amyloid-beta (Aβ)-positive patients is essential for Alzheimer disease clinical trials and disease-modifying treatments but currently requires PET or CSF sampling. Previous MRI-based deep learning models using only...
Humans Retrospective Studies Magnetic Resonance Imaging Amyloid beta-Peptides Alzheimer Disease Sensitivity and Specificity Positron-Emission Tomography Female Aged Male Aged, 80 and over Middle Aged Deep Learning
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