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Radiographic Image Enhancement

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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...
Algorithms Breast Neoplasms Computer Simulation Data Interpretation, Statistical False Positive Reactions Female Humans Models, Statistical Neural Networks, Computer Pattern Recognition, Automated Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Sample Size Sensitivity and Specificity Stochastic Processes Supervised Machine Learning
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Sampling from Determinantal Point Processes for Scalable Manifold Learning.

Information processing in medical imaging : proceedings of the ... conference Jan 1, 2015
High computational costs of manifold learning prohibit its application for large datasets. A common strategy to overcome this problem is to perform dimensionality reduction on selected landmarks and to successively embed the entire dataset with the N...
Algorithms Artificial Intelligence Computer Simulation Data Interpretation, Statistical Head and Neck Neoplasms Humans Imaging, Three-Dimensional Models, Statistical Pattern Recognition, Automated Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Sample Size Sensitivity and Specificity Signal Processing, Computer-Assisted Tomography, X-Ray Computed
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Multi-scale Convolutional Neural Networks for Lung Nodule Classification.

Information processing in medical imaging : proceedings of the ... conference Jan 1, 2015
We investigate the problem of diagnostic lung nodule classification using thoracic Computed Tomography (CT) screening. Unlike traditional studies primarily relying on nodule segmentation for regional analysis, we tackle a more challenging problem on ...
Algorithms Humans Lung Neoplasms Neural Networks, Computer Pattern Recognition, Automated Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Reproducibility of Results Sensitivity and Specificity Solitary Pulmonary Nodule Tomography, X-Ray Computed
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Abdominal multi-organ segmentation from CT images using conditional shape-location and unsupervised intensity priors.

Medical image analysis Dec 1, 2015
This paper addresses the automated segmentation of multiple organs in upper abdominal computed tomography (CT) data. The aim of our study is to develop methods to effectively construct the conditional priors and use their prediction power for more ac...
Algorithms Humans Imaging, Three-Dimensional Pattern Recognition, Automated Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Radiography, Abdominal Reproducibility of Results Sensitivity and Specificity Tomography, X-Ray Computed Unsupervised Machine Learning Viscera
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Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box.

Medical image analysis Dec 1, 2015
In this paper, we tackle the problem of automatic classification of pulmonary peri-fissural nodules (PFNs). The classification problem is formulated as a machine learning approach, where detected nodule candidates are classified as PFNs or non-PFNs. ...
Algorithms Humans Imaging, Three-Dimensional Lung Neoplasms Neural Networks, Computer Pattern Recognition, Automated Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Sensitivity and Specificity Software Solitary Pulmonary Nodule Subtraction Technique Tomography, X-Ray Computed
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Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom.

Pediatric radiology Mar 1, 2016
BACKGROUND: CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT.
Child, Preschool Computer Simulation Female Humans Knowledge Bases Machine Learning Male Models, Statistical Phantoms, Imaging Radiation Dosage Radiation Exposure Radiation Protection Radiographic Image Enhancement Reproducibility of Results Sensitivity and Specificity Subtraction Technique Tomography, X-Ray Computed
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Adapting content-based image retrieval techniques for the semantic annotation of medical images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 1, 2016
The automatic annotation of medical images is a prerequisite for building comprehensive semantic archives that can be used to enhance evidence-based diagnosis, physician education, and biomedical research. Annotation also has important applications i...
Algorithms Data Mining Database Management Systems Documentation Humans Imaging, Three-Dimensional Liver Machine Learning Natural Language Processing Pattern Recognition, Automated Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Radiology Information Systems Reproducibility of Results Semantics Sensitivity and Specificity Terminology as Topic Tomography, X-Ray Computed
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Histogram-Based Discrimination of Intravenous Contrast in Abdominopelvic Computed Tomography.

Journal of computer assisted tomography Jan 1, 2016
OBJECTIVE: The aim of this study was to evaluate the accuracy of fully automated machine learning methods for detecting intravenous contrast in computed tomography (CT) studies of the abdomen and pelvis.
Administration, Intravenous Algorithms Artificial Intelligence Contrast Media Humans Logistic Models Pelvis Radiographic Image Enhancement Radiography, Abdominal Reproducibility of Results Tomography, X-Ray Computed
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Computer-aided diagnosis system for lung nodules based on computed tomography using shape analysis, a genetic algorithm, and SVM.

Medical & biological engineering & computing Aug 1, 2017
Lung cancer is the major cause of death among patients with cancer worldwide. This work is intended to develop a methodology for the diagnosis of lung nodules using images from the Image Database Consortium and Image Database Resource Initiative (LID...
Algorithms Female Humans Male Middle Aged Models, Genetic Pattern Recognition, Automated Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Sensitivity and Specificity Solitary Pulmonary Nodule Support Vector Machine Tomography, X-Ray Computed
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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...
Adult Aged Algorithms Carcinoma, Hepatocellular Computer Simulation Female Humans Knowledge Bases Liver Liver Neoplasms Machine Learning Male Middle Aged Models, Biological Multidetector Computed Tomography Neovascularization, Pathologic Pattern Recognition, Automated Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Republic of Korea Sensitivity and Specificity
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