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 :
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