AIMC Topic: Diffusion Magnetic Resonance Imaging
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Blip-up blip-down circular EPI (BUDA-cEPI) for distortion-free dMRI with rapid unrolled deep learning reconstruction.
Magnetic resonance imaging
Nov 19, 2024
PURPOSE: BUDA-cEPI has been shown to achieve high-quality, high-resolution diffusion magnetic resonance imaging (dMRI) with fast acquisition time, particularly when used in conjunction with S-LORAKS reconstruction. However, this comes at a cost of mo...
Deep learning based apparent diffusion coefficient map generation from multi-parametric MR images for patients with diffuse gliomas.
Medical physics
Nov 8, 2024
PURPOSE: Apparent diffusion coefficient (ADC) maps derived from diffusion weighted magnetic resonance imaging (DWI MRI) provides functional measurements about the water molecules in tissues. However, DWI is time consuming and very susceptible to imag...
Minimizing prostate diffusion weighted MRI examination time through deep learning reconstruction.
Clinical imaging
Nov 5, 2024
PURPOSE: To study the diagnostic image quality of high b-value diffusion weighted images (DWI) derived from standard and variably reduced datasets reconstructed with a commercially available deep learning reconstruction (DLR) algorithm.
Exploring the feasibility of FOCUS DWI with deep learning reconstruction for breast cancer diagnosis: A comparative study with conventional DWI.
PloS one
Oct 31, 2024
PURPOSE: This study compared field-of-view (FOV) optimized and constrained undistorted single-shot diffusion-weighted imaging (FOCUS DWI) with deep-learning-based reconstruction (DLR) to conventional DWI for breast imaging.
SDS-Net: A Synchronized Dual-Stage Network for Predicting Patients Within 4.5-h Thrombolytic Treatment Window Using MRI.
Journal of imaging informatics in medicine
Oct 28, 2024
Timely and precise identification of acute ischemic stroke (AIS) within 4.5 h is imperative for effective treatment decision-making. This study aims to construct a novel network that utilizes limited datasets to recognize AIS patients within this cri...
Impact of non-contrast-enhanced imaging input sequences on the generation of virtual contrast-enhanced breast MRI scans using neural network.
European radiology
Oct 25, 2024
OBJECTIVE: To investigate how different combinations of T1-weighted (T1w), T2-weighted (T2w), and diffusion-weighted imaging (DWI) impact the performance of virtual contrast-enhanced (vCE) breast MRI.
Clinical evaluation of accelerated diffusion-weighted imaging of rectal cancer using a denoising neural network.
European journal of radiology
Oct 24, 2024
BACKGROUND: To evaluate the effectiveness of a deep learning denoising approach to accelerate diffusion-weighted imaging (DWI) and thus improve diagnostic accuracy and image quality in restaging rectal MRI following total neoadjuvant therapy (TNT).
Deep Learning Classification of Ischemic Stroke Territory on Diffusion-Weighted MRI: Added Value of Augmenting the Input with Image Transformations.
Journal of imaging informatics in medicine
Sep 30, 2024
Our primary aim with this study was to build a patient-level classifier for stroke territory in DWI using AI to facilitate fast triage of stroke to a dedicated stroke center. A retrospective collection of DWI images of 271 and 122 consecutive acute i...
Deep learning enables accurate brain tissue microstructure analysis based on clinically feasible diffusion magnetic resonance imaging.
NeuroImage
Sep 22, 2024
Diffusion magnetic resonance imaging (dMRI) allows non-invasive assessment of brain tissue microstructure. Current model-based tissue microstructure reconstruction techniques require a large number of diffusion gradients, which is not clinically feas...
The application value of support vector machine model based on multimodal MRI in predicting IDH-1mutation and Ki-67 expression in glioma.
BMC medical imaging
Sep 16, 2024
PURPOSE: To investigate the application value of support vector machine (SVM) model based on diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) and amide proton transfer- weighted (APTW) imaging in predicting isocitrate dehydrogenase 1...
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