Automatic lung nodule matching on sequential CT images
Computers in Biology and Medicine
Computers in Biology and Medicine
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The objective of this study is to develop a computer-aided diagnosis (CAD) system to support comparative reading of sequential helical CT images for lung cancer screening without using film displays. The placement of pulmonary shadows between sequential helical CT images sometimes differs due to the changes in lung size and shape caused by inspiration. The proposed algorithm consists of two sections; identification of region of interest and the comparison of sequential CT images. We validated the effectiveness of the algorithm by its application to images from 60 subjects. The algorithm could compare the slice images correctly with respect to a physician's point of view. The experimental results indicate that the proposed algorithm is useful in increasing the efficiency of the mass screening process.