12 March 2009 Lung nodule detection in chest radiography: image components analysis
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We aimed to evaluate the effect of different components of chest image on performances of both human observer and channelized Fisher-Hotelling model (CFH) in nodule detection task. Irrelevant and relevant components were separated from clinical chest radiography by employing Principal Component Analysis (PCA) methods. Human observer performance was evaluated in two-alternative forced-choice (2AFC) on original clinical images and anatomical structure only images obtained by PCA methods. Channelized Fisher-Hotelling model with Laguerre-Gauss basis function was evaluated to predict human performance. We show that relevant component is the primary factor influencing on nodule detection in chest radiography. There is obvious difference of detectability between human observer and CFH model for nodule detection in images only containing anatomical structure. CFH model should be used more carefully.
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Tao Luo, Tao Luo, Xuanqin Mou, Xuanqin Mou, Ying Yang, Ying Yang, Hao Yan, Hao Yan, } "Lung nodule detection in chest radiography: image components analysis", Proc. SPIE 7263, Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment, 72631Q (12 March 2009); doi: 10.1117/12.813503; https://doi.org/10.1117/12.813503

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