DocumentCode :
2719881
Title :
Automatic segmentation of the diaphragm in non-contrast CT images
Author :
Yalamanchili, Raja ; Chittajallu, Deepak ; Balanca, Paul ; Tamarappoo, Balaji ; Berman, Daniel ; Dey, Damini ; Kakadiaris, Ioannis
Author_Institution :
Dept. of Comput. Sci., Univ. of Houston, Houston, TX, USA
fYear :
2010
fDate :
14-17 April 2010
Firstpage :
900
Lastpage :
903
Abstract :
The diaphragm is a thin double-domed muscle that separates the thoracic and abdominal cavities. An accurate delineation of the diaphragm surface will be useful in providing a good region of interest for segmentation problems pertaining to the thoracic and abdominal cavities. In this paper, we present a fully automatic 3D graph-based method for the segmentation of the diaphragm in non-contrast CT data. In particular, we reformulate the diaphragm segmentation problem as an optimal surface segmentation problem in a volumetric graph. Comparison of the results obtained using our method with manual segmentations performed by an expert on non-contrast cardiac CT scans of 7 randomly selected patients indicated an overlap of 94.20 ± 0.01%.
Keywords :
computerised tomography; graph theory; image segmentation; medical image processing; muscle; 3D graph based method; abdominal cavity; automatic diaphragm segmentation; diaphragm surface delineation; double domed muscle; noncontrast CT image; thoracic cavity; volumetric graph; Abdomen; Biomedical computing; Biomedical imaging; Computed tomography; Cost function; Image segmentation; Lungs; Muscles; Spline; Surface fitting; Diaphragm segmentation; max closure; non-contrast CT;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
Conference_Location :
Rotterdam
ISSN :
1945-7928
Print_ISBN :
978-1-4244-4125-9
Electronic_ISBN :
1945-7928
Type :
conf
DOI :
10.1109/ISBI.2010.5490132
Filename :
5490132
Link To Document :
بازگشت