AIMC Topic: Diffusion Magnetic Resonance Imaging
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Attention-Based Q-Space Deep Learning Generalized for Accelerated Diffusion Magnetic Resonance Imaging.
IEEE journal of biomedical and health informatics
Feb 10, 2025
Diffusion magnetic resonance imaging (dMRI) is a non-invasive method for capturing the microanatomical information of tissues by measuring the diffusion weighted signals along multiple directions, which is widely used in the quantification of microst...
An Artificial Intelligence Model Using Diffusion Basis Spectrum Imaging Metrics Accurately Predicts Clinically Significant Prostate Cancer.
The Journal of urology
Jan 27, 2025
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 ...
Integration of MRI radiomics and clinical data for preoperative prediction of vascular invasion in breast cancer: A deep learning approach.
Magnetic resonance imaging
Jan 27, 2025
BACKGROUND: Accurate preoperative prediction of vascular invasion in breast cancer is crucial for surgical planning and patient management. MRI radiomics has shown promise in enhancing diagnostic precision. This study aims to evaluate the effectivene...
Middle Aged
Deep Learning
Preoperative Care
Image Processing, Computer-Assisted
Diffusion Magnetic Resonance Imaging
Magnetic Resonance Imaging
Contrast Media
Humans
Adult
Neoplasm Invasiveness
Sensitivity and Specificity
Breast
Retrospective Studies
Breast Neoplasms
Image Interpretation, Computer-Assisted
Female
Radiomics
Aged
Motion-Compensated Multishot Pancreatic Diffusion-Weighted Imaging With Deep Learning-Based Denoising.
Investigative radiology
Jan 20, 2025
OBJECTIVES: Pancreatic diffusion-weighted imaging (DWI) has numerous clinical applications, but conventional single-shot methods suffer from off resonance-induced artifacts like distortion and blurring while cardiovascular motion-induced phase incons...
TagGen: Diffusion-based generative model for cardiac MR tagging super resolution.
Magnetic resonance in medicine
Jan 17, 2025
PURPOSE: The aim of the work is to develop a cascaded diffusion-based super-resolution model for low-resolution (LR) MR tagging acquisitions, which is integrated with parallel imaging to achieve highly accelerated MR tagging while enhancing the tag g...
Deep learning-based free-water correction for single-shell diffusion MRI.
Magnetic resonance imaging
Jan 17, 2025
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
Jan 9, 2025
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).
Deep Learning-Based Super-Resolution Reconstruction on Undersampled Brain Diffusion-Weighted MRI for Infarction Stroke: A Comparison to Conventional Iterative Reconstruction.
AJNR. American journal of neuroradiology
Jan 8, 2025
BACKGROUND AND PURPOSE: DWI is crucial for detecting infarction stroke. However, its spatial resolution is often limited, hindering accurate lesion visualization. Our aim was to evaluate the image quality and diagnostic confidence of deep learning (D...
Using deep learning to shorten the acquisition time of brain MRI in acute ischemic stroke: Synthetic T2W images generated from b0 images.
PloS one
Jan 6, 2025
OBJECTIVE: This study aimed to assess the feasibility of the deep learning in generating T2 weighted (T2W) images from diffusion-weighted imaging b0 images.
DDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jan 4, 2025
In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusion MRI, namely DDEvENet, for anatomical brain parcellation. The key innovation of DDEvENet is the design of an evidential deep learning framework to q...
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