Proceedings of the 2017 International Conference on Material Science, Energy and Environmental Engineering (MSEEE 2017)

Region of Interest Extraction of Medical Image based on Improved Region Growing Algorithm

Authors
Shanshan Sun, Runtong Zhang
Corresponding Author
Shanshan Sun
Available Online August 2017.
DOI
10.2991/mseee-17.2017.87How to use a DOI?
Keywords
Medical Image, region of interest, iteration algorithm, region growing algorithm.
Abstract

Medical images are usually made up of regions of interest (ROI) and background areas, relative to the background area, the ROI contains important diagnostic information. Although the ROI may not be large in the entire image area, it is of great significance for doctors' diagnosis, clinical treatment and pathological analysis. The purpose of the paper is to extract the ROI from the surrounding environment by extracting the features of the Medical image. The paper is aimed at splitting the medical image by combining iteration algorithm and region growing algorithm, thus can mark out the nidus clearly.

Copyright
© 2017, 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/).

Download article (PDF)

Volume Title
Proceedings of the 2017 International Conference on Material Science, Energy and Environmental Engineering (MSEEE 2017)
Series
Advances in Engineering Research
Publication Date
August 2017
ISBN
10.2991/mseee-17.2017.87
ISSN
2352-5401
DOI
10.2991/mseee-17.2017.87How to use a DOI?
Copyright
© 2017, 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/).

Cite this article

TY  - CONF
AU  - Shanshan Sun
AU  - Runtong Zhang
PY  - 2017/08
DA  - 2017/08
TI  - Region of Interest Extraction of Medical Image based on Improved Region Growing Algorithm
BT  - Proceedings of the 2017 International Conference on Material Science, Energy and Environmental Engineering (MSEEE 2017)
PB  - Atlantis Press
SP  - 471
EP  - 475
SN  - 2352-5401
UR  - https://doi.org/10.2991/mseee-17.2017.87
DO  - 10.2991/mseee-17.2017.87
ID  - Sun2017/08
ER  -