Lymph Node Image Segmentation Based on Improved FCM Clustering and Multi-threshold
Yanling Zhang, Yuejia Zhang, Li Li
Available Online March 2013.
- https://doi.org/10.2991/iccsee.2013.775How to use a DOI?
- fuzzy C-means (FCM) peak algorithm , multi-threshold algorithm,lymph node image segmentation
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/iccsee.2013.775 ID - Zhang2013/03 ER -