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

DOI

10.2991/iccsee.2013.775How to use a DOI?

Keywords

fuzzy C-means (FCM) peak algorithm , multi-threshold algorithm,lymph node image segmentation

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yanling Zhang
AU  - Yuejia Zhang
AU  - Li Li
PY  - 2013/03
DA  - 2013/03
TI  - Lymph Node Image Segmentation Based on Improved FCM Clustering and Multi-threshold
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 3002
EP  - 3005
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.775
DO  - 10.2991/iccsee.2013.775
ID  - Zhang2013/03
ER  -