Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications

Feature Extraction of Ground-Glass Opacity Nodules using Active Contour Model for Lung Cancer Detection

Authors
Yanli Miao, Jianming Wang, Weiwei Du, Yanhe Ma, Hong Zhang
Corresponding Author
Yanli Miao
Available Online January 2017.
DOI
https://doi.org/10.2991/icmmita-16.2016.240How to use a DOI?
Keywords
Feature of Ground-Glass Opacity Nodules; Active Contour Model; Lung Cancer Detection
Abstract
The proportion of the solid part portion in a GGO nodule is one of features to detect lung cancer. It is difficult to segment the solid part in a GGO nodule completely because tissues surrounding GGO nodules include some impurities like noises in image processing technology. This paper proposes Active Contour Model (ACM) to find the boundary of a GGO nodule because ACM algorithm can remove noises. The size of a GGO nodule can be computed based on the boundary of the GGO nodule. Expectation-Maximization (EM) algorithm can segment the no solid part in GGO nodules because no solid part and solid part have different densities. Experiments show ACM algorithm is more effective than EM algorithm to find the boundary of a GGO nodule. Moreover, our proposal also can reduce the burden of doctors because it can find the boundary of GGO nodules automatically.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2016 4th International Conference on Machinery, Materials and Information Technology Applications
Part of series
Advances in Computer Science Research
Publication Date
January 2017
ISBN
978-94-6252-285-5
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmmita-16.2016.240How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yanli Miao
AU  - Jianming Wang
AU  - Weiwei Du
AU  - Yanhe Ma
AU  - Hong Zhang
PY  - 2017/01
DA  - 2017/01
TI  - Feature Extraction of Ground-Glass Opacity Nodules using Active Contour Model for Lung Cancer Detection
BT  - 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.240
DO  - https://doi.org/10.2991/icmmita-16.2016.240
ID  - Miao2017/01
ER  -