DocumentCode
384102
Title
A method for automated extraction of aorta and pulmonary artery in the mediastinum using medial line models from 3D chest X-ray CT images without contrast materials
Author
Kitasaka, Takayuki ; Hasegawa, Jun-ichi ; Mori, Kensaku ; Toriwaki, Jun-ichiro
Author_Institution
Graduate Sch. of Eng., Nagoya Univ., Japan
Volume
3
fYear
2002
fDate
2002
Firstpage
273
Abstract
Proposes a method of automated extraction of aorta and pulmonary artery (PA) areas in the mediastinum from uncontrasted 3D chest X-ray CT images. The proposed method does not extract contours of these blood vessels directly, but extracts the medial line of each, vessel and recovers each vessel area. First, the process performs edge detection based on the local standard deviation to get edge areas of vessels. Second, the Euclidean distance transformation is applied for non-edge areas and the likelihood image of the center of vessels is obtained. Medial line models are deformed based upon the likelihood image so as to be fit to the center of each artery. The aorta and the PA areas are obtained by applying the reverse distance transformation to medial lines extracted above. We applied the proposed method to seven cases of uncontrasted 3D chest X-ray CT images. The experimental results showed that the aorta and the PA areas could be extracted satisfactorily.
Keywords
blood vessels; computerised tomography; edge detection; image segmentation; lung; medical image processing; 3D chest X-ray CT images; Euclidean distance transform; aorta; automated extraction; blood vessels; edge detection; likelihood image; local standard deviation; medial line models; mediastinum; pulmonary artery; reverse distance transformation; uncontrasted images; Arteries; Biomedical imaging; Blood vessels; Computed tomography; Diseases; Image edge detection; Image segmentation; Lungs; Respiratory system; X-ray imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-1695-X
Type
conf
DOI
10.1109/ICPR.2002.1047847
Filename
1047847
Link To Document