AIMC Topic: Radiographic Image Enhancement

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Breast cancer detection and classification in digital mammography based on Non-Subsampled Contourlet Transform (NSCT) and Super Resolution.

Computer methods and programs in biomedicine Jul 4, 2015
Breast cancer is one of the most perilous diseases among women. Breast screening is a method of detecting breast cancer at a very early stage which can reduce the mortality rate. Mammography is a standard method for the early diagnosis of breast canc...
Pattern Recognition, Automated Radiographic Image Enhancement Reproducibility of Results Sensitivity and Specificity Breast Neoplasms Sample Size Signal Processing, Computer-Assisted Fuzzy Logic Mammography Humans Machine Learning Algorithms Female
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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...
Radiographic Image Enhancement Pattern Recognition, Automated Rest Myocardial Perfusion Imaging Coronary Stenosis Sensitivity and Specificity Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Humans Tomography, X-Ray Computed Reproducibility of Results 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 Enhancement Radiography, Abdominal Liver Neoplasms Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Humans Machine Learning Reproducibility of Results Sensitivity and Specificity Algorithms Tomography, X-Ray Computed
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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...
Humans Machine Learning Sensitivity and Specificity Imaging, Three-Dimensional Fuzzy Logic Radiographic Image Interpretation, Computer-Assisted Algorithms Tomography, X-Ray Computed Reproducibility of Results Pattern Recognition, Automated Radiographic Image Enhancement Bronchography
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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...
Humans Machine Learning Radiography, Thoracic Radiographic Image Enhancement Lung Radiographic Image Interpretation, Computer-Assisted Lung Diseases, Interstitial Algorithms Pattern Recognition, Automated Tomography, X-Ray Computed Sensitivity and Specificity
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Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 24, 2015
The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also ...
Radiographic Image Enhancement Breast Neoplasms Female Pattern Recognition, Automated Support Vector Machine Humans Reproducibility of Results False Positive Reactions Mammography Models, Statistical Algorithms Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted Computer Simulation
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Segmentation of pulmonary nodules in computed tomography using a regression neural network approach and its application to the Lung Image Database Consortium and Image Database Resource Initiative dataset.

Medical image analysis Feb 23, 2015
We present new pulmonary nodule segmentation algorithms for computed tomography (CT). These include a fully-automated (FA) system, a semi-automated (SA) system, and a hybrid system. Like most traditional systems, the new FA system requires only a sin...
Radiography, Thoracic Algorithms Radiographic Image Enhancement Databases, Factual Tomography, X-Ray Computed Humans Sensitivity and Specificity Regression Analysis Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Neural Networks, Computer Lung Neoplasms Data Interpretation, Statistical Pattern Recognition, Automated Solitary Pulmonary Nodule
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2D-3D radiograph to cone-beam computed tomography (CBCT) registration for C-arm image-guided robotic surgery.

International journal of computer assisted radiology and surgery Dec 12, 2014
PURPOSE: C-arm radiographs are commonly used for intraoperative image guidance in surgical interventions. Fluoroscopy is a cost-effective real-time modality, although image quality can vary greatly depending on the target anatomy. Cone-beam computed ...
Cone-Beam Computed Tomography Imaging, Three-Dimensional Robotics Fluoroscopy Animals Surgery, Computer-Assisted Phantoms, Imaging Radiographic Image Enhancement
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Computer-aided diagnosis of malignant mammograms using Zernike moments and SVM.

Journal of digital imaging Jul 9, 2014
This work is directed toward the development of a computer-aided diagnosis (CAD) system to detect abnormalities or suspicious areas in digital mammograms and classify them as malignant or nonmalignant. Original mammogram is preprocessed to separate t...
Breast Neoplasms Support Vector Machine Mammography Radiographic Image Interpretation, Computer-Assisted Radiographic Image Enhancement Databases, Factual Female Reproducibility of Results Sensitivity and Specificity Humans
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PIAA: Pre-imaging all-round assistant for digital radiography.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2025
BACKGROUND: In radiography procedures, radiographers' suboptimal positioning and exposure parameter settings may necessitate image retakes, subjecting patients to unnecessary ionizing radiation exposure. Reducing retakes is crucial to minimize patien...
Humans Artificial Intelligence Patient Positioning Radiographic Image Enhancement
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