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
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