AIMC Topic: Deep Learning

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Application of Deep Learning to Predict Standardized Uptake Value Ratio and Amyloid Status on F-Florbetapir PET Using ADNI Data.

AJNR. American journal of neuroradiology Jun 4, 2020
BACKGROUND AND PURPOSE: Cortical amyloid quantification on PET by using the standardized uptake value ratio is valuable for research studies and clinical trials in Alzheimer disease. However, it is resource intensive, requiring co-registered MR imagi...
Ethylene Glycols Neuroimaging Fluorine Radioisotopes Plaque, Amyloid Male Deep Learning Image Processing, Computer-Assisted Aniline Compounds Positron-Emission Tomography Radiopharmaceuticals Alzheimer Disease Brain Female Aged Humans
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Radiomics for precision medicine: Current challenges, future prospects, and the proposal of a new framework.

Methods (San Diego, Calif.) Jun 3, 2020
The advancement of artificial intelligence concurrent with the development of medical imaging techniques provided a unique opportunity to turn medical imaging from mostly qualitative, to further quantitative and mineable data that can be explored for...
Humans Precision Medicine Reproducibility of Results Imaging, Three-Dimensional Deep Learning Image Processing, Computer-Assisted Decision Support Systems, Clinical
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Major Depressive Disorder Classification Based on Different Convolutional Neural Network Models: Deep Learning Approach.

Clinical EEG and neuroscience Jun 3, 2020
The human brain is characterized by complex structural, functional connections that integrate unique cognitive characteristics. There is a fundamental hurdle for the evaluation of both structural and functional connections of the brain and the effect...
Humans Neural Networks, Computer Male Middle Aged Depressive Disorder, Major Brain Female Adult Brain-Computer Interfaces Diagnosis, Computer-Assisted Deep Learning Electroencephalography
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DeepDTI: High-fidelity six-direction diffusion tensor imaging using deep learning.

NeuroImage Jun 3, 2020
Diffusion tensor magnetic resonance imaging (DTI) is unsurpassed in its ability to map tissue microstructure and structural connectivity in the living human brain. Nonetheless, the angular sampling requirement for DTI leads to long scan times and pos...
Diffusion Tensor Imaging Humans Image Processing, Computer-Assisted Connectome Neural Networks, Computer Nerve Net Brain Deep Learning
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Deep learning-based reconstruction of ultrasound images from raw channel data.

International journal of computer assisted radiology and surgery Jun 3, 2020
PURPOSE: We investigate the feasibility of reconstructing ultrasound images directly from raw channel data using a deep learning network. Starting from the raw data, we present the network the full measurement information, allowing for a more generic...
Phantoms, Imaging Contrast Media Reference Values Signal-To-Noise Ratio Reproducibility of Results Diagnosis, Computer-Assisted Deep Learning Ultrasonography Image Processing, Computer-Assisted Models, Theoretical Humans Algorithms
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Deep Learning Identifies Cardiomyocyte Nuclei With High Precision.

Circulation research Jun 3, 2020
Myocytes, Cardiac Cell Nucleus Immunohistochemistry Animals Integrases Deep Learning Indoles Image Processing, Computer-Assisted Microscopy Mice Mice, Transgenic Fluorescent Dyes Biomarkers Myosin Heavy Chains Troponin T Reproducibility of Results
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Deep learning for automated exclusion of cardiac CT examinations negative for coronary artery calcium.

European journal of radiology Jun 3, 2020
PURPOSE: Coronary artery calcium (CAC) score has shown to be an accurate predictor of future cardiovascular events. Early detection by CAC scoring might reduce the number of deaths by cardiovascular disease (CVD). Automatically excluding scans which ...
Middle Aged Deep Learning Calcinosis Risk Factors Aged Radiographic Image Interpretation, Computer-Assisted Humans Male Coronary Artery Disease Coronary Vessels Tomography, X-Ray Computed Female
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Deep learning for identification of critical regions associated with toxicities after liver stereotactic body radiation therapy.

Medical physics Jun 3, 2020
PURPOSE: Radiation therapy (RT) is prescribed for curative and palliative treatment for around 50% of patients with solid tumors. Radiation-induced toxicities of healthy organs accompany many RTs and represent one of the main limiting factors during ...
Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Radiosurgery Humans
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Particulate impurities in cell-based medicinal products traced by flow imaging microscopy combined with deep learning for image analysis.

Cytotherapy Jun 2, 2020
Cell-based medicinal products (CBMPs) are rapidly gaining importance in the treatment of life-threatening diseases. However, the analytical toolbox for characterization of CBMPs is limited. The aim of our study was to develop a method based on flow i...
Microscopy Humans Neural Networks, Computer Deep Learning
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Deep learning systems for detecting and classifying the presence of impacted supernumerary teeth in the maxillary incisor region on panoramic radiographs.

Oral surgery, oral medicine, oral pathology and oral radiology Jun 2, 2020
OBJECTIVE: This investigation aimed to verify and compare the performance of 3 deep learning systems for classifying maxillary impacted supernumerary teeth (ISTs) in patients with fully erupted incisors.
Humans Deep Learning Maxilla Radiography, Panoramic Tooth, Supernumerary Incisor Tooth, Impacted
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