期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2014
卷号：6
期号：09
页码：334-337
出版社：Engg Journals Publications
摘要：Image segmentation plays a vital role in medical image processing. Eventually, the proposed work is subjected to classify the tumour and non-tumour parts, followed by the segmentation of tumour region in PET scan images. Lung cancer has been the largest cause of cancer deaths. This paper focuses on Fuzzy C means algorithm for Lung tumour part segmentation of PET scan images to diagnose accurately the region of cancer. A PET scan can often detect cellular level metabolic changes at the earliest, whereas a CT or MRI detect changes a little later as the disease begins to cause changes in the structure of organs or tissues. Cancerous tumours are usually more active, have a higher metabolic rate than normal tissue, and appear differently on a PET scan. It has been shown that effective and automatic segmentation can be achieved with this method for lung and area for segmented tumour part is calculated.
关键词：Lung Cancer;Fuzzy C Means; PET scan;Segmentation
