TY - GEN
T1 - Automatic segmentation of liver from CT images using probabilistic atlas and template matching
AU - Chen, Yen Wei
AU - Foruzan, Amir H.
AU - Dong, Chunhua
AU - Tateyama, Tomoko
AU - Han, Xianhua
PY - 2014
Y1 - 2014
N2 - A framework is proposed for automatic liver segmentation from CT volumes using probabilistic atlases and template matching techniques. Probabilistic atlases of human anatomy have been widely used for organ segmentation, which is used as a prior probability in a Bayes framework. The challenge is how to register the atlas to the patient volume. In this paper, we propose a template matching based technique for probabilistic atlas based organ segmentation. In our proposed method, we first find a Region of Interest (ROI) of the organ, which is based on human anatomic structure, and then the probabilistic atlas is used as a template to find the organ in the ROI by the use of template matching.
AB - A framework is proposed for automatic liver segmentation from CT volumes using probabilistic atlases and template matching techniques. Probabilistic atlases of human anatomy have been widely used for organ segmentation, which is used as a prior probability in a Bayes framework. The challenge is how to register the atlas to the patient volume. In this paper, we propose a template matching based technique for probabilistic atlas based organ segmentation. In our proposed method, we first find a Region of Interest (ROI) of the organ, which is based on human anatomic structure, and then the probabilistic atlas is used as a template to find the organ in the ROI by the use of template matching.
UR - http://www.scopus.com/inward/record.url?scp=84902309880&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84902309880&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-405-3-412
DO - 10.3233/978-1-61499-405-3-412
M3 - Conference contribution
AN - SCOPUS:84902309880
SN - 9781614994046
T3 - Frontiers in Artificial Intelligence and Applications
SP - 412
EP - 420
BT - Smart Digital Futures 2014
PB - IOS Press BV
ER -