AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Information extraction from multi-institutional radiology reports.

Artificial intelligence in medicine Oct 3, 2015
OBJECTIVES: The radiology report is the most important source of clinical imaging information. It documents critical information about the patient's health and the radiologist's interpretation of medical findings. It also communicates information to ...
United States Models, Theoretical Predictive Value of Tests Natural Language Processing Machine Learning Databases, Factual Electronic Health Records Reproducibility of Results Information Storage and Retrieval Semantics Pattern Recognition, Automated Radiology Information Systems Medical Record Linkage Discriminant Analysis Radiographic Image Interpretation, Computer-Assisted Data Mining Humans Observer Variation
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Improving Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation.

IEEE transactions on medical imaging Sep 28, 2015
Automated computer-aided detection (CADe) has been an important tool in clinical practice and research. State-of-the-art methods often show high sensitivities at the cost of high false-positives (FP) per patient rates. We design a two-tiered coarse-t...
Humans Female Colonic Polyps Aged Neural Networks, Computer Male Lymph Nodes Young Adult Machine Learning Spinal Neoplasms Middle Aged Radiographic Image Interpretation, Computer-Assisted Adult Databases, Factual Adolescent Tomography, X-Ray Computed Child
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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 Sep 8, 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. ...
Software Algorithms Tomography, X-Ray Computed Reproducibility of Results Humans Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Radiographic Image Enhancement Subtraction Technique Sensitivity and Specificity Imaging, Three-Dimensional Lung Neoplasms Solitary Pulmonary Nodule
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Sample Selection for Training Cascade Detectors.

PloS one Jul 21, 2015
Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Training datasets are such that the positive set has few samples and/or the negative set should represe...
Mammography Area Under Curve Facial Recognition Radiographic Image Interpretation, Computer-Assisted Humans Pattern Recognition, Automated Female Pedestrians False Positive Reactions Artificial Intelligence Breast Neoplasms Algorithms ROC Curve Databases, Factual Computational Biology
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Abdominal multi-organ segmentation from CT images using conditional shape-location and unsupervised intensity priors.

Medical image analysis Jul 4, 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...
Radiographic Image Enhancement Radiography, Abdominal Algorithms Tomography, X-Ray Computed Reproducibility of Results Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Viscera Imaging, Three-Dimensional Unsupervised Machine Learning Humans
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Myocardial perfusion analysis in cardiac computed tomography angiographic images at rest.

Medical image analysis May 27, 2015
Cardiac computed tomography angiography (CTA) is a non-invasive method for anatomic evaluation of coronary artery stenoses. However, CTA is prone to artifacts that reduce the diagnostic accuracy to identify stenoses. Further, CTA does not allow for d...
Tomography, X-Ray Computed Reproducibility of Results Sensitivity and Specificity Coronary Angiography Rest Myocardial Perfusion Imaging Coronary Stenosis Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Radiographic Image Enhancement Humans Machine Learning Algorithms
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Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

Medical image analysis May 21, 2015
Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially...
Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Radiographic Image Enhancement Radiography, Abdominal Tomography, X-Ray Computed Humans Reproducibility of Results Machine Learning Sensitivity and Specificity Algorithms Liver Neoplasms
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A hybrid method for airway segmentation and automated measurement of bronchial wall thickness on CT.

Medical image analysis May 14, 2015
Inflammatory and infectious lung diseases commonly involve bronchial airway structures and morphology, and these abnormalities are often analyzed non-invasively through high resolution computed tomography (CT) scans. Assessing airway wall surfaces an...
Pattern Recognition, Automated Radiographic Image Enhancement Bronchography Sensitivity and Specificity Imaging, Three-Dimensional Fuzzy Logic Algorithms Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Reproducibility of Results Humans Machine Learning
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Computer-aided lung nodule recognition by SVM classifier based on combination of random undersampling and SMOTE.

Computational and mathematical methods in medicine Apr 6, 2015
In lung cancer computer-aided detection/diagnosis (CAD) systems, classification of regions of interest (ROI) is often used to detect/diagnose lung nodule accurately. However, problems of unbalanced datasets often have detrimental effects on the perfo...
Lung Neoplasms Support Vector Machine Cluster Analysis Solitary Pulmonary Nodule Tomography, X-Ray Computed Models, Statistical Humans Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Algorithms Diagnosis, Computer-Assisted Pattern Recognition, Automated Imaging, Three-Dimensional
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Locality-constrained Subcluster Representation Ensemble for lung image classification.

Medical image analysis Mar 24, 2015
In this paper, we propose a new Locality-constrained Subcluster Representation Ensemble (LSRE) model, to classify high-resolution computed tomography (HRCT) images of interstitial lung diseases (ILDs). Medical images normally exhibit large intra-clas...
Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Lung Diseases, Interstitial Pattern Recognition, Automated Radiography, Thoracic Machine Learning Humans Tomography, X-Ray Computed Algorithms Sensitivity and Specificity Lung
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