期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2018
卷号：6
期号：4
页码：3385-3391
DOI：10.15680/IJIRCCE.2018.0604033
出版社：S&S Publications
摘要：Lung cancer or lung carcinoma is a harmful lung tissues described by uncontrolled development of
strange cells that begin off in one or the two lungs.Computed-Tomography (CT) have made it an inexorably basic
modality for imaging of lung cancer. Location of lung nodule on CT examinations are challenging assignments for
radiologists since they need to look for irregularities in countless images and the lesions can be inconspicuous.
Variousstages ofdiagnosis procedure for automatic detection of lung nodules in CT images consists of Image
Acquisition, Image Enhancement and Segmentation of Lung Region.The main objective of this paper is effective
segmentation of lung region in CT image for the purpose of lung cancer detection in medical field of Oncology.
Normally in any Image pre-preparing step, enhances the image information by smothering unessential in-formations or
improving a few highlights critical for additionally handling. Segmentation of Lung Region can be employed using
Threshold Algorithm and k-means Clustering. In this procedure, primary point is to evacuate the segments that are a
part of the CT image other than lung regions. For working of diagnosis procedure, the DICOM Lung CT images are
obtained from LIDC dataset.
