@inproceedings{030111c5496445689d04ebeb92a885a1,
title = "Medical image segmentation by more sensitive adaptive thresholding",
abstract = "To make 3D surface model from medical images, segmentation is essential process. And, in the case that the HU(Hounsfield Unit) values of the object to be segmented varies in the image, adaptive thresholding segmentation is very efficient segmentation method. But in many cases, it shows insufficient sensitivity of segmentation that weak(dim) objects are not segmented. This problem is caused mainly by strong(bright) object nearby the weak object because adaptive thresholding makes high threshold due to strong object. In this study we present a more sensitive adaptive thresholding method overcoming this problem.",
keywords = "Adaptive, Image, Medical, Segmentation, Sensitive, Thresholding",
author = "Cheolhwan Kim and Jiyoung Yoon and Lee, {Yun Jung}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 6th International Conference on IT Convergence and Security, ICITCS 2016 ; Conference date: 26-09-2016 Through 29-09-2016",
year = "2016",
month = nov,
day = "9",
doi = "10.1109/ICITCS.2016.7740353",
language = "English",
series = "2016 6th International Conference on IT Convergence and Security, ICITCS 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2016 6th International Conference on IT Convergence and Security, ICITCS 2016",
address = "United States",
}