文章基本信息

标题：An Optimized ANFIS Classifier Approach for Screening of COPD from Chest CT Scans with Adaptive Median Filtering
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作者：K. Meenakshi Sundaram ; C.S.Ravichandran
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2014
卷号：5
期号：2
页码：1949-1957
出版社：TechScience Publications
摘要：In medical image processing, Chronic Obstructive Pulmonary Disease is a name that refers to two lung diseases; they are chronic bronchitis and emphysema. The name COPD is used since both diseases are characterized by impediment to airflow that interferes with normal breathing and the two frequently co-exist with each other. If COPD is detected earlier, the formation of lung cancer is prevented. CT scan may afford additional information and also it can provide further detailed images of parts of the body that cannot easily be seen on a normal chest radiograph. Many researchers have been developed different techniques to improve the performance of automatic screening process. This paper involves in improves the accuracy over the existing technique using the adaptive region growing property and ANFIS classifier. Initially, pre-processing is carried out for the input image using median filtering technique to make the image fit for further processing and to remove the noises. The contours of the image will be obtaining using region growing technique. The ANFIS classifier is optimized to speed up the process and to produce optimized result.. The classification will be carried out by the features which have been taken from the segmented image. The proposed technique is implemented in MATLAB and the performance is compared with the existing technique. From the experimental result it can be said that the proposed method achieved more accuracy as compared with existing techniques
关键词：Chronic obstructive pulmonary disease; ANFIS;classifier; Adaptive Median filtering; Local Gabor XOR Pattern;(LGXP)