Title :
Automatic segmentation of the left atrium from MRI images using salient feature and contour evolution
Author :
Liangjia Zhu ; Yi Gao ; Yezzi, Anthony ; MacLeod, R. ; Cates, J. ; Tannenbaum, Allen
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fDate :
Aug. 28 2012-Sept. 1 2012
Abstract :
We propose an automatic approach for segmenting the left atrium from MRI images. In particular, the thoracic aorta is detected and used as a salient feature to find a seed region that lies inside the left atrium. A hybrid energy that combines robust statistics and localized region intensity information is employed to evolve active contours from the seed region to capture the whole left atrium. The experimental results demonstrate the accuracy and robustness of our approach.
Keywords :
biomedical MRI; blood vessels; cardiology; feature extraction; image segmentation; medical image processing; MRI images; automatic image segmentation; contour evolution; left atrium; localized region intensity information; robust statistics; salient feature; thoracic aorta; Active contours; Biomedical imaging; Heart; Image segmentation; Magnetic resonance imaging; Robustness; Shape; Algorithms; Heart Atria; Humans; Magnetic Resonance Imaging;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6346648