Automatic detection of GGO candidate regions employing four statistical features on thoracic MDCT image

Abstract

Detection of abnormal areas such as lung nodule, ground glass opacity on multi detector computed tomography images is a difficult task for radiologists. It is because subtle lesions such as small lung nodules tend to be low in contrast, and a large number of computed tomography images require a long visual screening times. In order to detect the… (More)

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Cite this paper

@article{Katsumata2007AutomaticDO, title={Automatic detection of GGO candidate regions employing four statistical features on thoracic MDCT image}, author={Yasunori Katsumata and Yoshinori Itai and Shigeru Maeda}, journal={2007 International Conference on Control, Automation and Systems}, year={2007}, pages={1278-1281} }