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9 March 2011 A study on quantifying COPD severity by combining pulmonary function tests and CT image analysis
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This paper describes a novel method that can evaluate chronic obstructive pulmonary disease (COPD) severity by combining measurements of pulmonary function tests and measurements obtained from CT image analysis. There is no cure for COPD. However, with regular medical care and consistent patient compliance with treatments and lifestyle changes, the symptoms of COPD can be minimized and progression of the disease can be slowed. Therefore, many diagnosis methods based on CT image analysis have been proposed for quantifying COPD. Most of diagnosis methods for COPD extract the lesions as low-attenuation areas (LAA) by thresholding and evaluate the COPD severity by calculating the LAA in the lung (LAA%). However, COPD is usually the result of a combination of two conditions, emphysema and chronic obstructive bronchitis. Therefore, the previous methods based on only LAA% do not work well. The proposed method utilizes both of information including the measurements of pulmonary function tests and the results of the chest CT image analysis to evaluate the COPD severity. In this paper, we utilize a multi-class AdaBoost to combine both of information and classify the COPD severity into five stages automatically. The experimental results revealed that the accuracy rate of the proposed method was 88.9% (resubstitution scheme) and 64.4% (leave-one-out scheme).
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yukitaka Nimura, Takayuki Kitasaka, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, and Kensaku Mori "A study on quantifying COPD severity by combining pulmonary function tests and CT image analysis", Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 796330 (9 March 2011);

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