NDLI: Automatic detection of ground glass opacity from the thoracic MDCT images by using density features

Content Provider	IEEE Xplore Digital Library
Author	Hyoungseop Kim Nakashima, T. Itai, Y. Maeda, S. Joo kooi Tan Ishikawa, S.
Copyright Year	2007
Description	Author affiliation: Kyushu Inst. of Technol., Kitakyushu (Hyoungseop Kim; Nakashima, T.; Itai, Y.; Maeda, S.; Joo kooi Tan; Ishikawa, S.)
Abstract	Automatic detection of abnormal shadow area on a multi detector CT image is important task under developing a computer aided diagnosis system. Ground glass opacity is one of the important features in lung cancer diagnosis of computer aided diagnosis. It may be seen as diffuse or more often as patchy in distribution taking sometimes a geographic or mosaic distribution. A large number of diseases can be associated with GGO on CT image. We propose a technique for automatic detection of ground glass opacity from the segmented lung regions by computer based on a set of the thoracic CT images. In this paper, we segment the lung region for extraction of the region of interest employing binarization and labeling process from the inputted each slices images. The region having the largest area is regarded as the tentative lung regions. Furthermore, the ground glass opacity is classified by correlation distribution on the successive slice from the extracted lung region with respect to the thoracic CT images. Experiment is performed employing 32 thoracic CT image sets and 71.7% of recognition rates were achieved. Obtained results are shown along with a discussion.
Starting Page	1274
Ending Page	1277
File Size	767587
Page Count	4
File Format	PDF
ISBN	9788995003862
DOI	10.1109/ICCAS.2007.4406532
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-17
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	ICASE
Subject Keyword	Glass Cancer detection Linear Discriminant Function Ground Glass Opacity Diseases Image segmentation Image analysis Lungs Computed tomography Detectors Attenuation Tophat Transformation Biomedical imaging
Content Type	Text
Resource Type	Article

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