AIMC Topic: Magnetic Resonance Imaging

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Attenuation correction using deep Learning and integrated UTE/multi-echo Dixon sequence: evaluation in amyloid and tau PET imaging.

European journal of nuclear medicine and molecular imaging
PURPOSE: PET measures of amyloid and tau pathologies are powerful biomarkers for the diagnosis and monitoring of Alzheimer's disease (AD). Because cortical regions are close to bone, quantitation accuracy of amyloid and tau PET imaging can be signifi...

Designing individual-specific and trial-specific models to accurately predict the intensity of nociceptive pain from single-trial fMRI responses.

NeuroImage
Using machine learning to predict the intensity of pain from fMRI has attracted rapidly increasing interests. However, due to remarkable inter- and intra-individual variabilities in pain responses, the performance of existing fMRI-based pain predicti...

Simulator-generated training datasets as an alternative to using patient data for machine learning: An example in myocardial segmentation with MRI.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Supervised Machine Learning techniques have shown significant potential in medical image analysis. However, the training data that need to be collected for these techniques in the field of MRI 1) may not be available, 2) may...

Clinical utility of deep learning motion correction for T1 weighted MPRAGE MR images.

European journal of radiology
PURPOSE: To evaluate the clinical utility of the application of a deep learning motion correction technique on 3D MPRAGE magnetic resonance images acquired in routine clinical practice.

Deep learning reconstruction for cardiac magnetic resonance fingerprinting T and T mapping.

Magnetic resonance in medicine
PURPOSE: To develop a deep learning method for rapidly reconstructing T and T maps from undersampled electrocardiogram (ECG) triggered cardiac magnetic resonance fingerprinting (cMRF) images.

Deep-learning-based segmentation of the vocal tract and articulators in real-time magnetic resonance images of speech.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Magnetic resonance (MR) imaging is increasingly used in studies of speech as it enables non-invasive visualisation of the vocal tract and articulators, thus providing information about their shape, size, motion and position....

Potential Candidates for Focal Therapy in Prostate Cancer in the Era of Magnetic Resonance Imaging-targeted Biopsy: A Large Multicenter Cohort Study.

European urology focus
BACKGROUND: Focal therapy (FT) with its favorable side-effect profile represents an option between active surveillance and traditional whole-gland treatment in localized prostate cancer (PCa). Consensus statements recommend eligibility criteria based...

Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet.

Medical physics
PURPOSE: Contouring intraprostatic lesions is a prerequisite for dose-escalating these lesions in radiotherapy to improve the local cancer control. In this study, a deep learning-based approach was developed for automatic intraprostatic lesion segmen...

Population Graph-Based Multi-Model Ensemble Method for Diagnosing Autism Spectrum Disorder.

Sensors (Basel, Switzerland)
With the advancement of brain imaging techniques and a variety of machine learning methods, significant progress has been made in brain disorder diagnosis, in particular Autism Spectrum Disorder. The development of machine learning models that can di...