AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Myocardial perfusion analysis in cardiac computed tomography angiographic images at rest.

Medical image analysis
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...

Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

Medical image analysis
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...

A hybrid method for airway segmentation and automated measurement of bronchial wall thickness on CT.

Medical image analysis
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...

Computer-aided lung nodule recognition by SVM classifier based on combination of random undersampling and SMOTE.

Computational and mathematical methods in medicine
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...

Locality-constrained Subcluster Representation Ensemble for lung image classification.

Medical image analysis
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...

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
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 ...

Improving the Mann-Whitney statistical test for feature selection: an approach in breast cancer diagnosis on mammography.

Artificial intelligence in medicine
OBJECTIVE: This work addresses the theoretical description and experimental evaluation of a new feature selection method (named uFilter). The uFilter improves the Mann-Whitney U-test for reducing dimensionality and ranking features in binary classifi...

Three-dimensional SVM with latent variable: application for detection of lung lesions in CT images.

Journal of medical systems
The study aims to improve the performance of current computer-aided schemes for the detection of lung lesions, especially the low-contrast in gray density or irregular in shape. The relative position between suspected lesion and whole lung is, for th...