AIMC Topic:
Image Interpretation, Computer-Assisted

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3D Deep Learning Angiography (3D-DLA) from C-arm Conebeam CT.

AJNR. American journal of neuroradiology Mar 22, 2018
BACKGROUND AND PURPOSE: Deep learning is a branch of artificial intelligence that has demonstrated unprecedented performance in many medical imaging applications. Our purpose was to develop a deep learning angiography method to generate 3D cerebral a...
Humans Tomography, X-Ray Computed Deep Learning Artifacts Cerebral Angiography Imaging, Three-Dimensional Image Interpretation, Computer-Assisted
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Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

Acta biotheoretica Mar 21, 2018
Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as ...
Neural Networks, Computer Algorithms Biomass Image Interpretation, Computer-Assisted Fourier Analysis Cameroon Color
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Evaluation of a miniaturized NIR spectrometer for cultivar identification: The case of barley, chickpea and sorghum in Ethiopia.

PloS one Mar 21, 2018
Crop cultivar identification is fundamental for agricultural research, industry and policies. This paper investigates the feasibility of using visible/near infrared hyperspectral data collected with a miniaturized NIR spectrometer to identify cultiva...
Cicer Humans Image Interpretation, Computer-Assisted Support Vector Machine Sorghum Spectroscopy, Near-Infrared Ethiopia Hordeum Discriminant Analysis
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Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.

Journal of healthcare engineering Mar 19, 2018
Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic ...
Image Interpretation, Computer-Assisted Brain Neoplasms Humans Glioma Neural Networks, Computer Magnetic Resonance Imaging Algorithms
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Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study.

JACC. Cardiovascular imaging Mar 14, 2018
OBJECTIVES: The study evaluated the automatic prediction of obstructive disease from myocardial perfusion imaging (MPI) by deep learning as compared with total perfusion deficit (TPD).
Aged, 80 and over Male Middle Aged Humans Female Aged Radiopharmaceuticals Image Interpretation, Computer-Assisted Organophosphorus Compounds Tomography, Emission-Computed, Single-Photon Deep Learning Predictive Value of Tests Registries Technetium Tc 99m Sestamibi Organotechnetium Compounds Coronary Circulation Myocardial Perfusion Imaging Coronary Stenosis
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Biomedical image classification based on a cascade of an SVM with a reject option and subspace analysis.

Computers in biology and medicine Mar 12, 2018
Automated biomedical image classification could confront the challenges of high level noise, image blur, illumination variation and complicated geometric correspondence among various categorical biomedical patterns in practice. To handle these challe...
Support Vector Machine Diagnostic Imaging Image Interpretation, Computer-Assisted Humans Databases, Factual ROC Curve
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Medical Image Synthesis with Deep Convolutional Adversarial Networks.

IEEE transactions on bio-medical engineering Mar 9, 2018
Medical imaging plays a critical role in various clinical applications. However, due to multiple considerations such as cost and radiation dose, the acquisition of certain image modalities may be limited. Thus, medical image synthesis can be of great...
Humans Brain Magnetic Resonance Imaging Tomography, X-Ray Computed Deep Learning Pelvis Image Interpretation, Computer-Assisted
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Artificial neural network retrained to detect myocardial ischemia using a Japanese multicenter database.

Annals of nuclear medicine Mar 7, 2018
PURPOSE: An artificial neural network (ANN) has been applied to detect myocardial perfusion defects and ischemia. The present study compares the diagnostic accuracy of a more recent ANN version (1.1) with the initial version 1.0.
Radiopharmaceuticals Japan Quality Improvement Coronary Angiography Heart Neural Networks, Computer Cardiac Surgical Procedures Artificial Intelligence Female ROC Curve Aged Myocardial Ischemia Humans Area Under Curve Myocardial Perfusion Imaging Image Interpretation, Computer-Assisted Male Tomography, Emission-Computed, Single-Photon Organotechnetium Compounds Databases as Topic Endovascular Procedures
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Acral melanoma detection using a convolutional neural network for dermoscopy images.

PloS one Mar 7, 2018
BACKGROUND/PURPOSE: Acral melanoma is the most common type of melanoma in Asians, and usually results in a poor prognosis due to late diagnosis. We applied a convolutional neural network to dermoscopy images of acral melanoma and benign nevi on the h...
Humans Neural Networks, Computer Image Interpretation, Computer-Assisted Melanoma Skin Sensitivity and Specificity Foot Skin Neoplasms Hand Early Detection of Cancer Dermoscopy
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Deep Learning and Its Applications in Biomedicine.

Genomics, proteomics & bioinformatics Mar 6, 2018
Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the und...
Genomics Computational Biology Proteins Protein Structure, Secondary Diagnostic Imaging Image Interpretation, Computer-Assisted Neural Networks, Computer Machine Learning Algorithms Humans
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