AIMC Topic: Magnetic Resonance Imaging

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DeepEOR: automated perioperative volumetric assessment of variable grade gliomas using deep learning.

Acta neurochirurgica Dec 19, 2022
PURPOSE: Volumetric assessments, such as extent of resection (EOR) or residual tumor volume, are essential criterions in glioma resection surgery. Our goal is to develop and validate segmentation machine learning models for pre- and postoperative mag...
Brain Neoplasms Deep Learning Humans Algorithms Magnetic Resonance Imaging Image Processing, Computer-Assisted Glioma
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Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient-Recalled Echo (qGRE) magnetic resonance imaging metrics associated with human brain neuronal structure and hemodynamic properties.

NMR in biomedicine Dec 18, 2022
The purpose of the current study was to introduce a Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) method for reconstructing quantitative maps of biological tissue cellular-specific, R2t*, and hemodynamic-specific, R2', metri...
Humans Brain Magnetic Resonance Imaging Signal-To-Noise Ratio Hemodynamics Deep Learning
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Ensemble learning and personalized training for the improvement of unsupervised deep learning-based synthetic CT reconstruction.

Medical physics Dec 17, 2022
BACKGROUND: The growing adoption of magnetic resonance imaging (MRI)-guided radiation therapy (RT) platforms and a focus on MRI-only RT workflows have brought the technical challenge of synthetic computed tomography (sCT) reconstruction to the forefr...
Humans Tomography, X-Ray Computed Magnetic Resonance Imaging Radiotherapy, Image-Guided Deep Learning Image Processing, Computer-Assisted
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An Artificial Intelligence Tool for Clinical Decision Support and Protocol Selection for Brain MRI.

AJNR. American journal of neuroradiology Dec 15, 2022
BACKGROUND AND PURPOSE: Protocolling, the process of determining the most appropriate acquisition parameters for an imaging study, is time-consuming and produces variable results depending on the performing physician. The purpose of this study was to...
Neuroimaging Humans Decision Support Systems, Clinical Magnetic Resonance Imaging Artificial Intelligence Brain
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A comparative study between deep learning and radiomics models in grading liver tumors using hepatobiliary phase contrast-enhanced MR images.

BMC medical imaging Dec 14, 2022
PURPOSE: To compare a deep learning model with a radiomics model in differentiating high-grade (LR-3, LR-4, LR-5) liver imaging reporting and data system (LI-RADS) liver tumors from low-grade (LR-1, LR-2) LI-RADS tumors based on the contrast-enhanced...
Humans Magnetic Resonance Imaging Retrospective Studies Liver Neoplasms Deep Learning Carcinoma, Hepatocellular
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Deep learning-based motion quantification from k-space for fast model-based magnetic resonance imaging motion correction.

Medical physics Dec 13, 2022
BACKGROUND: Intra-scan rigid-body motion is a costly and ubiquitous problem in clinical magnetic resonance imaging (MRI) of the head.
Motion Retrospective Studies Artifacts Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Minimizing the effect of white matter lesions on deep learning based tissue segmentation for brain volumetry.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 13, 2022
Automated methods for segmentation-based brain volumetry may be confounded by the presence of white matter (WM) lesions, which introduce abnormal intensities that can alter the classification of not only neighboring but also distant brain tissue. The...
Image Processing, Computer-Assisted Reproducibility of Results Humans Multiple Sclerosis Magnetic Resonance Imaging Deep Learning Brain White Matter
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Editorial for "Automated MR Image Prescription of the Liver Using Deep Learning: Development, Evaluation, and Prospective Implementation".

Journal of magnetic resonance imaging : JMRI Dec 12, 2022
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Liver Humans Prospective Studies
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Automated brain tumour segmentation from multi-modality magnetic resonance imaging data based on new particle swarm optimisation segmentation method.

The international journal of medical robotics + computer assisted surgery : MRCAS Dec 12, 2022
BACKGROUND: Segmentation of brain tumours is a complex problem in medical image processing and analysis. It is a time-consuming and error-prone task. Therefore, computer-aided detection systems need to be developed to decrease physicians' workload an...
Algorithms Brain Neoplasms Humans Artificial Intelligence Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Artificial intelligence algorithms aimed at characterizing or detecting prostate cancer on MRI: How accurate are they when tested on independent cohorts? - A systematic review.

Diagnostic and interventional imaging Dec 12, 2022
PURPOSE: The purpose of this study was to perform a systematic review of the literature on the diagnostic performance, in independent test cohorts, of artificial intelligence (AI)-based algorithms aimed at characterizing/detecting prostate cancer on ...
Magnetic Resonance Imaging Prostatic Neoplasms Artificial Intelligence Algorithms Humans Male Diagnosis, Computer-Assisted
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