DocumentCode
2722633
Title
Automatic segmentation of pathological tissues in cardiac MRI
Author
Elagouni, Khaoula ; Ciofolo-Veit, Cybèle ; Mory, Benoît
Author_Institution
Philips Med. Syst. Res. Paris, Suresnes, France
fYear
2010
fDate
14-17 April 2010
Firstpage
472
Lastpage
475
Abstract
In the context of cardiac viability assessment, we propose a new fully automatic method to segment and quantify myocardial pathological tissues in Late Enhancement Cardiac Magnetic Resonance images. Our two main contributions are a generic image intensity analysis and an original variational segmentation method, the Fast Region Competition. The obtained results are robust to anatomical variability and partial volume effects and false positives are avoided. To validate our results, we use representations that are independent of myocardium shape and size and compute clinically relevant indicators. The proposed method was tested on 100 slices and compared to other classical segmentation approaches, showing the best agreement with semi-automatic expert delineations.
Keywords
biomedical MRI; cardiology; diseases; image segmentation; medical image processing; muscle; statistical analysis; anatomical variability; automatic segmentation; cardiac MRI; cardiac magnetic resonance; cardiac viability; fast region competition; image intensity analysis; late enhancement; myocardial pathological tissue; myocardium shape; myocardium size; myocardium viability; partial volume effects; variational method; variational segmentation method; Image analysis; Image segmentation; Magnetic analysis; Magnetic resonance; Magnetic resonance imaging; Myocardium; Pathology; Robustness; Shape; Testing; Segmentation; lateenhancement; myocardium viability; variational methods;
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.2010.5490306
Filename
5490306
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