Paper
9 March 2011 Computer-aided assessment of pulmonary disease in novel swine-origin H1N1 influenza on CT
Jianhua Yao, Andrew J. Dwyer, Ronald M. Summers, Daniel J. Mollura
Author Affiliations +
Abstract
The 2009 pandemic is a global outbreak of novel H1N1 influenza. Radiologic images can be used to assess the presence and severity of pulmonary infection. We develop a computer-aided assessment system to analyze the CT images from Swine-Origin Influenza A virus (S-OIV) novel H1N1 cases. The technique is based on the analysis of lung texture patterns and classification using a support vector machine (SVM). Pixel-wise tissue classification is computed from the SVM value. The method was validated on four H1N1 cases and ten normal cases. We demonstrated that the technique can detect regions of pulmonary abnormality in novel H1N1 patients and differentiate these regions from visually normal lung (area under the ROC curve is 0.993). This technique can also be applied to differentiate regions infected by different pulmonary diseases.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jianhua Yao, Andrew J. Dwyer, Ronald M. Summers, and Daniel J. Mollura "Computer-aided assessment of pulmonary disease in novel swine-origin H1N1 influenza on CT", Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79632W (9 March 2011); https://doi.org/10.1117/12.878030
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KEYWORDS
Lung

Image segmentation

Image classification

Chest

CAD systems

Computer aided diagnosis and therapy

Statistical analysis

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