NDLI: Image Feature Analysis of Lymph Node Based on Cloud-Model and FCM Clustering

Content Provider	IEEE Xplore Digital Library
Author	Yanling Zhang Minghao Zhang Li Li
Copyright Year	2013
Description	Author affiliation: Sch. of Comput., Guangzhou Univ., Guangzhou, China (Yanling Zhang; Minghao Zhang) \|\| Sun Yat-sen Univ. Cancer Center, Guangzhou, China (Li Li)
Abstract	Lymph node is one of the important organs as the immunologic filter in the body. The pathological change of lymph node is an important basis of malignant tumor detection and judgment of metastasis of cancer (lung cancer, colorectal cancer, breast cancer, liver cancer, cervical cancer, etc.). Therefore, the feature analysis of lymph node is meaningful for the forecast about tumor recrudescence and metastasis. Based on image features, lymph node characters and advice from doctors, the sixteen features including shape, texture and grey are extracted and analyzed using cloud model. Eight helpful features (the largest area ratio, length to diameter ratio, the area ratio of length to diameter, the standard deviation of the internal texture changes, standard differential gray, gray consistency, low density values, high density value) for classification of benign and malignant lymph nodes are filtered to recognize pelvic lymph nodes. Improved FCM clustering algorithm is used to detect classification results of eight features achieved by cloud model analysis. Experiment results show that the clustering classification ability of eight features selected by cloud model can achieve an average recognition rate of 70% which is better than that of other features. So the eight features can be used for computer-aided classification and recognition system of pelvic lymph nodes.
Starting Page	633
Ending Page	638
File Size	216593
Page Count	6
File Format	PDF
e-ISBN	9781479921416
DOI	10.1109/EIDWT.2013.114
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape feature Cloud model Texture feature FCM clustering Gray image feature
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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