AIMC Topic: Magnetic Resonance Imaging
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MRI image synthesis for fluid-attenuated inversion recovery and diffusion-weighted images with deep learning.
Physical and engineering sciences in medicine
Jan 30, 2023
This study aims to synthesize fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted images (DWI) with a deep conditional adversarial network from T1- and T2-weighted magnetic resonance imaging (MRI) images. A total of 1980 images of 102 ...
An Overview of Deep Learning Methods for Left Ventricle Segmentation.
Computational intelligence and neuroscience
Jan 30, 2023
Cardiac health diseases are one of the key causes of death around the globe. The number of heart patients has considerably increased during the pandemic. Therefore, it is crucial to assess and analyze the medical and cardiac images. Deep learning arc...
Direct machine learning reconstruction of respiratory variation waveforms from resting state fMRI data in a pediatric population.
NeuroImage
Jan 26, 2023
In many functional magnetic resonance imaging (fMRI) studies, respiratory signals are unavailable or do not have acceptable quality due to issues with subject compliance, equipment failure or signal error. In large databases, such as the Human Connec...
Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging.
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Jan 26, 2023
The application of machine learning (ML) and deep learning (DL) in radiology has expanded exponentially. In recent years, an extremely large number of studies have reported about the hepatobiliary domain. Its applications range from differential diag...
Auto-segmentation of the tibia and femur from knee MR images via deep learning and its application to cartilage strain and recovery.
Journal of biomechanics
Jan 26, 2023
The ability to efficiently and reproducibly generate subject-specific 3D models of bone and soft tissue is important to many areas of musculoskeletal research. However, methodologies requiring such models have largely been limited by lengthy manual s...
MRI-based two-stage deep learning model for automatic detection and segmentation of brain metastases.
European radiology
Jan 25, 2023
OBJECTIVES: To develop and validate a two-stage deep learning model for automatic detection and segmentation of brain metastases (BMs) in MRI images.
Can MRI Be Used as a Sensor to Record Neural Activity?
Sensors (Basel, Switzerland)
Jan 25, 2023
Magnetic resonance provides exquisite anatomical images and functional MRI monitors physiological activity by recording blood oxygenation. This review attempts to answer the following question: Can MRI be used as a sensor to directly record neural be...
Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging.
Journal of magnetic resonance imaging : JMRI
Jan 24, 2023
BACKGROUND: Determination of H3 K27M mutation in diffuse midline glioma (DMG) is key for prognostic assessment and stratifying patient subgroups for clinical trials. MRI can noninvasively depict morphological and metabolic characteristics of H3 K27M ...
Free-breathing and instantaneous abdominal T mapping via single-shot multiple overlapping-echo acquisition and deep learning reconstruction.
European radiology
Jan 24, 2023
OBJECTIVES: To develop a real-time abdominal T mapping method without requiring breath-holding or respiratory-gating.
Weakly supervised perivascular spaces segmentation with salient guidance of Frangi filter.
Magnetic resonance in medicine
Jan 24, 2023
PURPOSE: To develop a weakly supervised 3D perivascular spaces (PVS) segmentation model that combines the filter-based image processing algorithm and the convolutional neural network.
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