AI Medical Compendium Topic:
Radiographic Image Interpretation, Computer-Assisted

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Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network.

Medical physics Mar 1, 2017
PURPOSE: It is estimated that 7% of women in the western world will develop palpable breast cysts in their lifetime. Even though cysts have been correlated with risk of developing breast cancer, many of them are benign and do not require follow-up. W...
Humans Neural Networks, Computer Female Area Under Curve Radiographic Image Interpretation, Computer-Assisted Datasets as Topic False Positive Reactions Breast Cyst Breast Neoplasms ROC Curve Mammography Diagnosis, Differential
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Unsupervised consensus cluster analysis of [18F]-fluoroethyl-L-tyrosine positron emission tomography identified textural features for the diagnosis of pseudoprogression in high-grade glioma.

Oncotarget Jan 31, 2017
RATIONALE: Timely detection of pseudoprogression (PSP) is crucial for the management of patients with high-grade glioma (HGG) but remains difficult. Textural features of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) mirror ...
Humans Retrospective Studies Kaplan-Meier Estimate Tyrosine Neoplasm Grading Radiographic Image Interpretation, Computer-Assisted Radiopharmaceuticals Disease-Free Survival Pilot Projects Brain Neoplasms Time Factors Male Treatment Outcome Middle Aged Female Glioma Disease Progression Magnetic Resonance Imaging Reproducibility of Results Aged Cluster Analysis Adult Unsupervised Machine Learning Predictive Value of Tests Positron Emission Tomography Computed Tomography
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Enhancement of digital radiography image quality using a convolutional neural network.

Journal of X-ray science and technology Jan 1, 2017
Digital radiography system is widely used for noninvasive security check and medical imaging examination. However, the system has a limitation of lower image quality in spatial resolution and signal to noise ratio. In this study, we explored whether ...
Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Radiographic Image Enhancement Humans Neural Networks, Computer Reproducibility of Results
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Adapting to Artificial Intelligence: Radiologists and Pathologists as Information Specialists.

JAMA Dec 13, 2016
Pathologists Data Mining Image Interpretation, Computer-Assisted Pattern Recognition, Automated Information Services Machine Learning Radiology Radiologists Radiographic Image Interpretation, Computer-Assisted Humans Computers, Mainframe Artificial Intelligence
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Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique.

Medical physics Jun 1, 2016
PURPOSE: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional e...
Humans Radiographic Image Interpretation, Computer-Assisted Whole Body Imaging Lung ROC Curve Lung Neoplasms Support Vector Machine Positron Emission Tomography Computed Tomography Neural Networks, Computer Female Sensitivity and Specificity Male
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Comparison of Knowledge-based Iterative Model Reconstruction and Hybrid Reconstruction Techniques for Liver CT Evaluation of Hypervascular Hepatocellular Carcinoma.

Journal of computer assisted tomography Jan 1, 2016
OBJECTIVE: The purpose of this work was to evaluate the image quality, lesion conspicuity, and dose reduction provided by knowledge-based iterative model reconstruction (IMR) in computed tomography (CT) of the liver compared with hybrid iterative rec...
Radiographic Image Interpretation, Computer-Assisted Models, Biological Knowledge Bases Neovascularization, Pathologic Pattern Recognition, Automated Multidetector Computed Tomography Radiographic Image Enhancement Middle Aged Liver Neoplasms Carcinoma, Hepatocellular Liver Aged Adult Sensitivity and Specificity Male Humans Machine Learning Algorithms Computer Simulation Republic of Korea Female Reproducibility of Results
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Automatic Detection of Masses in Mammograms Using Quality Threshold Clustering, Correlogram Function, and SVM.

Journal of digital imaging Jun 1, 2015
Breast cancer is the second most common type of cancer in the world. Several computer-aided detection and diagnosis systems have been used to assist health experts and to indicate suspect areas that would be difficult to perceive by the human eye; th...
Sensitivity and Specificity Breast Neoplasms ROC Curve Image Processing, Computer-Assisted Support Vector Machine Cluster Analysis Mammography Radiographic Image Interpretation, Computer-Assisted Humans Algorithms Female
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Comparative analysis of breast cancer detection in mammograms and thermograms.

Biomedizinische Technik. Biomedical engineering Feb 1, 2015
In this paper, we present a system based on feature extraction techniques for detecting abnormal patterns in digital mammograms and thermograms. A comparative study of texture-analysis methods is performed for three image groups: mammograms from the ...
Thermography Breast Neoplasms Mammography Machine Learning Radiographic Image Interpretation, Computer-Assisted Algorithms Observer Variation Humans Female Reproducibility of Results Sensitivity and Specificity
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Restricted Boltzmann machines based oversampling and semi-supervised learning for false positive reduction in breast CAD.

Bio-medical materials and engineering Jan 1, 2015
The false-positive reduction (FPR) is a crucial step in the computer aided detection system for the breast. The issues of imbalanced data distribution and the limitation of labeled samples complicate the classification procedure. To overcome these ch...
Models, Statistical Supervised Machine Learning Female Humans Sample Size Pattern Recognition, Automated Reproducibility of Results Neural Networks, Computer Data Interpretation, Statistical False Positive Reactions Sensitivity and Specificity Algorithms Radiographic Image Interpretation, Computer-Assisted Stochastic Processes Breast Neoplasms Computer Simulation Radiographic Image Enhancement
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On the Automated Segmentation of Epicardial and Mediastinal Cardiac Adipose Tissues Using Classification Algorithms.

Studies in health technology and informatics Jan 1, 2015
The quantification of fat depots on the surroundings of the heart is an accurate procedure for evaluating health risk factors correlated with several diseases. However, this type of evaluation is not widely employed in clinical practice due to the re...
Reproducibility of Results Sensitivity and Specificity Adipose Tissue Pericardium Radiographic Image Interpretation, Computer-Assisted Humans Subtraction Technique Pattern Recognition, Automated Machine Learning Mediastinum Algorithms Tomography, X-Ray Computed
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