AIMC Topic: Magnetic Resonance Imaging

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A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions.

European journal of radiology Feb 12, 2022
BACKGROUND: For patients with meningioma, surgical procedures are different because of the status of sinus invasion. However, there is still no suitable technique to identify the status of sinus invasion in patients with meningiomas. We aimed to buil...
Humans Magnetic Resonance Imaging Meningioma Meningeal Neoplasms Retrospective Studies Deep Learning
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Application of Deep Learning to Ischemic and Hemorrhagic Stroke Computed Tomography and Magnetic Resonance Imaging.

Seminars in ultrasound, CT, and MR Feb 11, 2022
Deep Learning (DL) algorithm holds great potential in the field of stroke imaging. It has been applied not only to the "downstream" side such as lesion detection, treatment decision making, and outcome prediction, but also to the "upstream" side for ...
Hemorrhagic Stroke Magnetic Resonance Imaging Stroke Tomography, X-Ray Computed Deep Learning
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Abnormal Degree Centrality as a Potential Imaging Biomarker for Right Temporal Lobe Epilepsy: A Resting-state Functional Magnetic Resonance Imaging Study and Support Vector Machine Analysis.

Neuroscience Feb 11, 2022
Previous studies have reported altered neuroimaging features in right temporal lobe epilepsy (rTLE). However, the alterations in degree centrality (DC) as a diagnostic method for rTLE have not been reported. Therefore, we aimed to explore abnormaliti...
Magnetic Resonance Imaging Brain Mapping Epilepsy, Temporal Lobe Temporal Lobe Brain Support Vector Machine Humans Biomarkers
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An efficient magnetic resonance image data quality screening dashboard.

Journal of applied clinical medical physics Feb 11, 2022
PURPOSE: Complex data processing and curation for artificial intelligence applications rely on high-quality data sets for training and analysis. Manually reviewing images and their associated annotations is a very laborious task and existing quality ...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Data Accuracy Artificial Intelligence Brain Neoplasms Humans
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Deep learning-based high-accuracy quantitation for lumbar intervertebral disc degeneration from MRI.

Nature communications Feb 11, 2022
To help doctors and patients evaluate lumbar intervertebral disc degeneration (IVDD) accurately and efficiently, we propose a segmentation network and a quantitation method for IVDD from T2MRI. A semantic segmentation network (BianqueNet) composed of...
Intervertebral Disc Magnetic Resonance Imaging Spine Intervertebral Disc Degeneration Intervertebral Disc Displacement Lumbar Vertebrae Male Deep Learning Humans Female
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Convolutional Neural Networks for Segmenting Cerebellar Fissures from Magnetic Resonance Imaging.

Sensors (Basel, Switzerland) Feb 10, 2022
The human cerebellum plays an important role in coordination tasks. Diseases such as spinocerebellar ataxias tend to cause severe damage to the cerebellum, leading patients to a progressive loss of motor coordination. The detection of such damages ca...
Cerebellum Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Humans Brain
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Highly Efficient and Accurate Deep Learning-Based Classification of MRI Contrast on a CPU and GPU.

Journal of digital imaging Feb 9, 2022
Classifying MR images based on their contrast mechanism can be useful in image segmentation where additional information from different contrast mechanisms can improve intensity-based segmentation and help separate the class distributions. In additio...
Humans Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Automatic segmentation of magnetic resonance images for high-dose-rate cervical cancer brachytherapy using deep learning.

Medical physics Feb 9, 2022
PURPOSE: Magnetic resonance (MR) imaging is the gold standard in image-guided brachytherapy (IGBT) due to its superior soft-tissue contrast for target and organs-at-risk (OARs) delineation. Accurate and fast segmentation of MR images are very importa...
Female Uterine Cervical Neoplasms Radiotherapy Planning, Computer-Assisted Deep Learning Humans Brachytherapy Magnetic Resonance Imaging Radiotherapy Dosage
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Robust-Deep: A Method for Increasing Brain Imaging Datasets to Improve Deep Learning Models' Performance and Robustness.

Journal of digital imaging Feb 8, 2022
A small dataset commonly affects generalization, robustness, and overall performance of deep neural networks (DNNs) in medical imaging research. Since gathering large clinical databases is always difficult, we proposed an analytical method for produc...
Deep Learning Neuroimaging Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Positron Emission Tomography Computed Tomography Brain
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[Not Available].

Zeitschrift fur medizinische Physik Feb 7, 2022
Spoke trajectory parallel transmit (pTX) excitation in ultra-high field MRI enables B inhomogeneities arising from the shortened RF wavelength in biological tissue to be mitigated. To this end, current RF excitation pulse design algorithms either emp...
Deep Learning Magnetic Resonance Imaging Brain Computer Simulation Calibration Phantoms, Imaging Algorithms
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