AIMC Topic: Magnetic Resonance Imaging
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Artificial intelligence-driven 3D MRI of lumbosacral nerve root anomalies: accuracy, incidence, and clinical utility.
Neuroradiology
Mar 1, 2025
PURPOSE: Lumbosacral nerve root anomalies are relatively rare but can be a risk factor for intraoperative nerve injury. However, it is often difficult to evaluate them with preoperative imaging. We developed a software that automatically generates th...
AI-powered prostate cancer detection: a multi-centre, multi-scanner validation study.
European radiology
Feb 28, 2025
OBJECTIVES: Multi-centre, multi-vendor validation of artificial intelligence (AI) software to detect clinically significant prostate cancer (PCa) using multiparametric magnetic resonance imaging (MRI) is lacking. We compared a new AI solution, valida...
Comprehensive evaluation of pipelines for classification of psychiatric disorders using multi-site resting-state fMRI datasets.
Neural networks : the official journal of the International Neural Network Society
Feb 28, 2025
Objective classification biomarkers that are developed using resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for psychiatric disorders. Unfortunately, no widely accepted biomar...
Denoising Diffusion Probabilistic Model to Simulate Contrast-enhanced spinal MRI of Spinal Tumors: A Multi-Center Study.
Academic radiology
Feb 28, 2025
RATIONALE AND OBJECTIVES: To generate virtual T1 contrast-enhanced (T1CE) sequences from plain spinal MRI sequences using the denoising diffusion probabilistic model (DDPM) and to compare its performance against one baseline model pix2pix and three a...
Humans
Algorithms
Adult
Sensitivity and Specificity
Male
Middle Aged
Computer Simulation
Female
Reproducibility of Results
Aged
Diffusion Magnetic Resonance Imaging
Artifacts
Contrast Media
Spinal Neoplasms
Magnetic Resonance Imaging
Image Enhancement
Models, Statistical
Signal-To-Noise Ratio
Image Interpretation, Computer-Assisted
Graph-based prototype inverse-projection for identifying cortical sulcal pattern abnormalities in congenital heart disease.
Medical image analysis
Feb 28, 2025
Examining the altered arrangement and patterning of sulcal folds offers insights into the mechanisms of neurodevelopmental differences in psychiatric and neurological disorders. Previous sulcal pattern analysis used spectral graph matching of sulcal ...
A Generative Shape Compositional Framework to Synthesize Populations of Virtual Chimeras.
IEEE transactions on neural networks and learning systems
Feb 28, 2025
Generating virtual organ populations that capture sufficient variability while remaining plausible is essential to conduct in silico trials (ISTs) of medical devices. However, not all anatomical shapes of interest are always available for each indivi...
Enhanced U-Net for Infant Brain MRI Segmentation: A (2+1)D Convolutional Approach.
Sensors (Basel, Switzerland)
Feb 28, 2025
BACKGROUND: Infant brain tissue segmentation from MRI data is a critical task in medical imaging, particularly challenging due to the evolving nature of tissue contrasts in the early months of life. The difficulty increases as gray matter (GM) and wh...
Preoperative diagnosis of meningioma sinus invasion based on MRI radiomics and deep learning: a multicenter study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Feb 28, 2025
OBJECTIVE: Exploring the construction of a fusion model that combines radiomics and deep learning (DL) features is of great significance for the precise preoperative diagnosis of meningioma sinus invasion.
Repeatability-encouraging self-supervised learning reconstruction for quantitative MRI.
Magnetic resonance in medicine
Feb 27, 2025
PURPOSE: The clinical value of quantitative MRI hinges on its measurement repeatability. Deep learning methods to reconstruct undersampled quantitative MRI can accelerate reconstruction but do not aim to promote quantitative repeatability. This study...
AutoDPS: An unsupervised diffusion model based method for multiple degradation removal in MRI.
Computer methods and programs in biomedicine
Feb 27, 2025
BACKGROUND AND OBJECTIVE: Diffusion models have demonstrated their ability in image generation and solving inverse problems like restoration. Unlike most existing deep-learning based image restoration techniques which rely on unpaired or paired data ...
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