Lymph Node Image Segmentation Based on Improved FCM Clustering and Multi-Threshold

Author:

Zhang Yan Ling1,Zhang Yue Jia1,Li Li2

Affiliation:

1. Guangzhou University

2. Sun Yat-sen University Cancer Center Guangzhou

Abstract

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.) An algorithm of lymph node image segmentation based on improved FCM clustering and multi-threshold is proposed to segment the lymph CT image with blurred edge. First, the improved FCM peak clustering is used to sharpen the fuzzy boundary of lymph CT image effectively. Then the multi-threshold algorithm based on image entropy change is introduced to segment enhanced images. The experiment shows that the above algorithm can obtain better segmentation results compared with the traditional FCM clustering method in the case of the fuzzy edge of the lymph node tissue.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Reference10 articles.

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3. Canny J. A computational approach to edge detection[J]. IEEE PAMI, 1986, 8(6) : 679-698.

4. David N. Olivieri,Francisco Vega. Image Prototype Similarity Matching for Lymph Node Hemopathology. Proceedings of the International Conference on Pattern Recognition (ICPR'00) [C]. 2000: 1051-4651.

5. Zhang Jun-hua, WangYuan-yuan. Analysis and application for sonographic image of cervical lymph node[D]. [doctor dissertation]. Fu Dan University, 2007: 5-24.

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