Lung nodules detection in chest radiography: image components analysis
2009
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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