AIMC Topic: Magnetic Resonance Imaging
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Development and web deployment of an automated neuroradiology MRI protocoling tool with natural language processing.
BMC medical informatics and decision making
Jul 12, 2021
BACKGROUND: A systematic approach to MRI protocol assignment is essential for the efficient delivery of safe patient care. Advances in natural language processing (NLP) allow for the development of accurate automated protocol assignment. We aim to de...
Deep Learning Network for Segmentation of the Prostate Gland With Median Lobe Enlargement in T2-weighted MR Images: Comparison With Manual Segmentation Method.
Current problems in diagnostic radiology
Jul 11, 2021
PURPOSE: Aim of this study was to evaluate a fully automated deep learning network named Efficient Neural Network (ENet) for segmentation of prostate gland with median lobe enlargement compared to manual segmentation.
Deep-learning-based attenuation correction in dynamic [O]HO studies using PET/MRI in healthy volunteers.
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Jul 11, 2021
Quantitative [O]HO positron emission tomography (PET) is the accepted reference method for regional cerebral blood flow (rCBF) quantification. To perform reliable quantitative [O]HO-PET studies in PET/MRI scanners, MRI-based attenuation-correction (M...
The divided brain: Functional brain asymmetry underlying self-construal.
NeuroImage
Jul 9, 2021
Self-construal (orientations of independence and interdependence) is a fundamental concept that guides human behaviour, and it is linked to a large number of brain regions. However, understanding the connectivity of these regions and the critical pri...
Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology.
Computer methods and programs in biomedicine
Jul 9, 2021
BACKGROUND AND OBJECTIVE: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. I...
Aggregation-and-Attention Network for brain tumor segmentation.
BMC medical imaging
Jul 9, 2021
BACKGROUND: Glioma is a malignant brain tumor; its location is complex and is difficult to remove surgically. To diagnosis the brain tumor, doctors can precisely diagnose and localize the disease using medical images. However, the computer-assisted d...
MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping.
NeuroImage
Jul 8, 2021
Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse problem relating the tissue phase to the underlying susceptibility dis...
3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning.
Computer methods and programs in biomedicine
Jul 8, 2021
BACKGROUND AND OBJECTIVES: Deep learning is being increasingly used for deformable image registration and unsupervised approaches, in particular, have shown great potential. However, the registration of abdominopelvic Computed Tomography (CT) images ...
Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy.
Circulation
Jul 7, 2021
BACKGROUND: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for noninvasive myocardial tissue characterization but requires intravenous contrast agent administration. It is highly desired to deve...
Versatile Convolutional Networks Applied to Computed Tomography and Magnetic Resonance Image Segmentation.
Journal of medical systems
Jul 7, 2021
Medical image segmentation has seen positive developments in recent years but remains challenging with many practical obstacles to overcome. The applications of this task are wide-ranging in many fields of medicine, and used in several imaging modali...
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