AI Medical Compendium Journal:
NMR in biomedicine

Showing 11 to 20 of 76 articles

DF-QSM: Data Fidelity based Hybrid Approach for Improved Quantitative Susceptibility Mapping of the Brain.

NMR in biomedicine
Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique to quantify the magnetic susceptibility of the tissue under investigation. Deep learning methods have shown promising results in deconvolving the susc...

Intravoxel incoherent motion and diffusion kurtosis imaging and their machine-learning-based texture analysis for detection and assessment of prostate cancer severity at 3 T.

NMR in biomedicine
OBJECTIVES: To evaluate the role of combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) and their machine-learning-based texture analysis for the detection and assessment of severity in prostate cancer (PCa).

A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation.

NMR in biomedicine
Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with applications in disease diagnostics, intervention, and treatment planning. Accurate MRI segmentation is critical for diagnosing abnormalities, monitoring diseases, and d...

Recurrent neural network-based simultaneous cardiac T1, T2, and T1ρ mapping.

NMR in biomedicine
The purpose of the current study was to explore the feasibility of training a deep neural network to accelerate the process of generating T1, T2, and T1ρ maps for a recently proposed free-breathing cardiac multiparametric mapping technique, where a r...

Deep-learning-based super-resolution for accelerating chemical exchange saturation transfer MRI.

NMR in biomedicine
Chemical exchange saturation transfer (CEST) MRI is a molecular imaging tool that provides physiological information about tissues, making it an invaluable tool for disease diagnosis and guided treatment. Its clinical application requires the acquisi...

A review of ADHD detection studies with machine learning methods using rsfMRI data.

NMR in biomedicine
Attention deficit hyperactivity disorder (ADHD) is a common mental health condition that significantly affects school-age children, causing difficulties with learning and daily functioning. Early identification is crucial, and reliable and objective ...

Dynamic parametric MRI and deep learning: Unveiling renal pathophysiology through accurate kidney size quantification.

NMR in biomedicine
Renal pathologies often manifest as alterations in kidney size, providing a valuable avenue for employing dynamic parametric MRI as a means to derive kidney size measurements for the diagnosis, treatment, and monitoring of renal disease. Furthermore,...

High-resolution spiral real-time cardiac cine imaging with deep learning-based rapid image reconstruction and quantification.

NMR in biomedicine
The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) and deep learning (DL)-based segmentation approach to quantify the left ventricular ejection fraction (LVEF) for high-reso...

Fast deep learning reconstruction techniques for preclinical magnetic resonance fingerprinting.

NMR in biomedicine
We propose a deep learning (DL) model and a hyperparameter optimization strategy to reconstruct T and T maps acquired with the magnetic resonance fingerprinting (MRF) methodology. We applied two different MRF sequence routines to acquire images of ex...

Deep learning based correction of RF field induced inhomogeneities for T2w prostate imaging at 7 T.

NMR in biomedicine
At ultrahigh field strengths images of the body are hampered by B -field inhomogeneities. These present themselves as inhomogeneous signal intensity and contrast, which is regarded as a "bias field" to the ideal image. Current bias field correction m...