Study on the effective segmentation algorithm of image lesion areas in Department of Internal Medicine

DOI

10.2991/amcce-15.2015.202How to use a DOI?

Keywords

visceral adhesions; image segmentation; Department of internal medicine;

Abstract

The effective segmentation algorithm of image lesion areas in Department of Internal Medicine is an important problem in the field of medical imaging. The current segmentation techniques of image lesion areas in Department of Internal Medicine are using the difference characters of edge pixels, due to visceral adhesions, the segmentation threshold is difficult to be accurately defined, and the precision is low. Therefore, this paper proposed a segmentation method of image lesion areas in Department of Internal Medicine based on improved cuckoo search algorithm to optimize maximum entropy. Firstly, by the maximum entropy method to find segmentation objective function of image lesion areas in Department of internal medicine, then the improved cuckoo search algorithm is adopted to optimize the objective function, find the best segmentation position of image lesion area in Department of internal medicine, so as to achieve image lesion area segmentation, finally multiple images of internal medicine are utilized to conduct simulation experiment, in order to test the performance of the proposed algorithm. The results show that, this method not only solves the defects existing in the traditional segmentation algorithm, while improving the precision of image lesion area of internal medicine, has better robustness, and better practical value.

Copyright

© 2015, 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  - Aiqin Zhang
PY  - 2015/04
DA  - 2015/04
TI  - Study on the effective segmentation algorithm of image lesion areas in Department of Internal Medicine
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 655
EP  - 659
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.202
DO  - 10.2991/amcce-15.2015.202
ID  - Zhang2015/04
ER  -