DocumentCode :
5549
Title :
Automatic 3-D Segmentation of Endocardial Border of the Left Ventricle From Ultrasound Images
Author :
Santiago, Carlos ; Nascimento, Jacinto C. ; Marques, Jorge S.
Author_Institution :
Inst. for Syst. & Robot., Inst. Super. Tecnico, Lisbon, Portugal
Volume :
19
Issue :
1
fYear :
2015
fDate :
Jan. 2015
Firstpage :
339
Lastpage :
348
Abstract :
The segmentation of the left ventricle (LV) is an important task to assess the cardiac function in ultrasound images of the heart. This paper presents a novel methodology for the segmentation of the LV in three-dimensional (3-D) echocardiographic images based on the probabilistic data association filter (PDAF). The proposed methodology begins by initializing a 3-D deformable model either semiautomatically, with user input, or automatically, and it comprises the following feature hierarchical approach: 1) edge detection in the vicinity of the surface (low-level features); 2) edge grouping to obtain potential LV surface patches (mid-level features); and 3) patch filtering using a shape-PDAF framework (high-level features). This method provides good performance accuracy in 20 echocardiographic volumes, and compares favorably with the state-of-the-art segmentation methodologies proposed in the recent literature.
Keywords :
associative processing; echocardiography; edge detection; feature extraction; filters; hierarchical systems; image segmentation; medical image processing; pattern clustering; physiological models; probability; LV segmentation; automatic 3D segmentation; cardiac function assessment; echocardiographic volume; edge detection; edge grouping; endocardial border segmentation; feature hierarchical approach; heart ultrasound image; high-level feature; left ventricle segmentation; low-level feature; mid-level feature; patch filtering; performance accuracy; potential LV surface patch; probabilistic data association filter; semiautomatic 3D deformable model initialization; shape-PDAF framework; three-dimensional echocardiographic image; user input; Computational modeling; Deformable models; Feature extraction; Image edge detection; Image segmentation; Solid modeling; Three-dimensional displays; 3-D echocardiography; deformable models; image segmentation; left ventricle (LV); robust estimation;
fLanguage :
English
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
Publisher :
ieee
ISSN :
2168-2194
Type :
jour
DOI :
10.1109/JBHI.2014.2308424
Filename :
6748865
Link To Document :
بازگشت