A Non-parametric Probabilistic Model for Hepatic Tumor Detection
Authors
Y. Konno, X.H Han, Y.W Chen, X. Wei
Corresponding Author
Y. Konno
Available Online June 2015.
- DOI
- 10.2991/cisia-15.2015.158How to use a DOI?
- Keywords
- non-parametric; probability model; gaussian mixture model; tumor detection
- Abstract
Automatic hepatic tumor enhancement and detection in CT volume data is an important preprocessing step in computer-aided diagnosis of liver tumor. In this paper, we proposed a novel non-parametric probabilistic model for automatic tumor detection. Compared with conventional method such as Gaussian mixture model, our proposed method is parameter-free method and can be applied to abnormal livers even with different type tumors. The proposed method is easy to implement and the computation cost is also low compared with other method.
- 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/).
Cite this article
TY - CONF AU - Y. Konno AU - X.H Han AU - Y.W Chen AU - X. Wei PY - 2015/06 DA - 2015/06 TI - A Non-parametric Probabilistic Model for Hepatic Tumor Detection BT - Proceedings of the International Conference on Computer Information Systems and Industrial Applications PB - Atlantis Press SP - 581 EP - 584 SN - 2352-538X UR - https://doi.org/10.2991/cisia-15.2015.158 DO - 10.2991/cisia-15.2015.158 ID - Konno2015/06 ER -