DocumentCode :
3512594
Title :
Improved 3D automatic segmentation and measurement of pleural effusions
Author :
Bliton, John ; Yao, Jianhua ; Bi, Mark ; Summers, Ronald M.
Author_Institution :
Radiol. & Image Sci. Dept., Nat. Institutes of Health, Bethesda, MD, USA
fYear :
2011
fDate :
March 30 2011-April 2 2011
Firstpage :
1954
Lastpage :
1957
Abstract :
Pleural effusions are accumulations of fluid in the pleural space, usually associated with atelectasis of the adjacent lung. We have previously presented an automated method to measure the volume of pleural effusions on chest CT images. This paper presents an improved version of the same method, which adds 3D surface modeling and additional propagation of the segmentation in the inferior direction. The improved method is also more robust to noise. We compared this method to manual segmentations and the previous method by applying it to 15 chest CT scans. The new segmentation, on average, increased estimated effusion volume by 11%, bringing it closer to the expected average. In addition, the correlation between manual and automatic effusion volumes increased from .59 to .81 (p = .13), indicating a better segmentation.
Keywords :
biological fluid dynamics; computerised tomography; diseases; image segmentation; lung; medical image processing; 3D automatic segmentation; 3D surface modeling; atelectasis; chest CT images; effusion volume; lung; pleural effusions; Computed tomography; Image segmentation; Lungs; Manuals; Pixel; Surface morphology; Three dimensional displays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
Conference_Location :
Chicago, IL
ISSN :
1945-7928
Print_ISBN :
978-1-4244-4127-3
Electronic_ISBN :
1945-7928
Type :
conf
DOI :
10.1109/ISBI.2011.5872792
Filename :
5872792
Link To Document :
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