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Diffusion Magnetic Resonance Imaging

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Brain Age Analysis and Dementia Classification using Convolutional Neural Networks trained on Diffusion MRI: Tests in Indian and North American Cohorts.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Deep learning models based on convolutional neural networks (CNNs) have been used to classify Alzheimer's disease or infer dementia severity from T1-weighted brain MRI scans. Here, we examine the value of adding diffusion-weighted MRI (dMRI) as an in...

An Artificial Intelligence Model Using Diffusion Basis Spectrum Imaging Metrics Accurately Predicts Clinically Significant Prostate Cancer.

The Journal of urology
PURPOSE: Conventional prostate magnetic resonance imaging has limited accuracy for clinically significant prostate cancer (csPCa). We performed diffusion basis spectrum imaging (DBSI) before biopsy and applied artificial intelligence models to these ...

Deep learning-based free-water correction for single-shell diffusion MRI.

Magnetic resonance imaging
Free-water elimination (FWE) modeling in diffusion magnetic resonance imaging (dMRI) is crucial for accurate estimation of diffusion properties by mitigating the partial volume effects caused by free water, particularly at the interface between white...

Estimation of TP53 mutations for endometrial cancer based on diffusion-weighted imaging deep learning and radiomics features.

BMC cancer
OBJECTIVES: To construct a prediction model based on deep learning (DL) and radiomics features of diffusion weighted imaging (DWI), and clinical variables for evaluating TP53 mutations in endometrial cancer (EC).

Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning.

Scientific reports
Diffusion magnetic resonance imaging (diffusion MRI) is widely employed to probe the diffusive motion of water molecules within the tissue. Numerous diseases and processes affecting the central nervous system can be detected and monitored via diffusi...

Image quality and diagnostic performance of deep learning reconstruction for diffusion- weighted imaging in 3 T breast MRI.

European journal of radiology
PURPOSE: This study aimed to assess the image quality and the diagnostic value of deep learning reconstruction (DLR) for diffusion-weighted imaging (DWI) compared with conventional single-shot echo-planar imaging (ss-EPI) in 3 T breast MRI.

Deep learning-based classification of diffusion-weighted imaging-fluid-attenuated inversion recovery mismatch.

Scientific reports
The presence of a diffusion-weighted imaging (DWI)-fluid-attenuated inversion recovery (FLAIR) mismatch holds potential value in identifying candidates for recanalization treatment. However, the visual assessment of DWI-FLAIR mismatch is subject to l...

Diffusion-Weighted Imaging-Based Radiomics Features and Machine Learning Method to Predict the 90-Day Prognosis in Patients With Acute Ischemic Stroke.

The neurologist
OBJECTIVES: The evaluation of the prognosis of patients with acute ischemic stroke (AIS) is of great significance in clinical practice. We aim to evaluate the feasibility and effectiveness of diffusion-weighted imaging (DWI) image-based radiomics fea...

Automated Imaging Differentiation for Parkinsonism.

JAMA neurology
IMPORTANCE: Magnetic resonance imaging (MRI) paired with appropriate disease-specific machine learning holds promise for the clinical differentiation of Parkinson disease (PD), multiple system atrophy (MSA) parkinsonian variant, and progressive supra...