Title :
P3A-5 3D Segmentation of the Heart Muscle in Real-Time 3D Echocardiographic Sequences Using Image Statistics
Author :
Nillesen, M.M. ; Lopata, R.G.P. ; Gerrits, I.H. ; Kapusta, L. ; Huisman, H.J. ; Thijssen, J.M. ; de Korte, C.L.
Author_Institution :
Clinical Phys. Lab., Radboud Univ. Nijmegen Med. Centre
Abstract :
A fully automated segmentation of the endocardial surface was developed by integrating spatio-temporal information of 3D ultrasound image sequences. 3D echocardiographic image sequences of the left ventricle of five healthy children were obtained in transthoracic short/long axis view. 2D and 3D (adaptive) filtering was used to reduce speckle noise and optimize the distinction between blood and myocardium, while preserving sharpness of edges between various structures. Four different filters (2D adaptive mean, 2D and 3D adaptive mean squares filter and 2D local entropy) were tested. The filter kernel was related to speckle size to yield statistically robust data. Filter quality was measured by comparing overlap percentages of histograms of manually segmented blood and myocardial regions. ROC curves of manually segmented blood regions were determined to compare effects of the different filters. A deformable contour algorithm was used, after automatic thresholding, to yield a closed contour of the endocardial border in each elevational plane. Each contour was optimized using contours of surrounding spatio-temporal planes as limiting condition to ensure spatio-temporal. The combination of adaptive filtering using image statistics and deformable contours has potential to segment the endocardial surface in 3D
Keywords :
adaptive filters; echocardiography; image segmentation; image sequences; medical image processing; 2D adaptive filtering; 2D adaptive mean filter; 2D adaptive mean squares filter; 2D local entropy filter; 3D adaptive filtering; 3D adaptive mean squares filter; 3D segmentation; 3D ultrasound image sequences; ROC curves; automatic thresholding; blood; deformable contour algorithm; endocardial surface; filter kernel; filter quality; heart muscle; image statistics; myocardium; real-time 3D echocardiographic sequences; speckle noise; Adaptive filters; Blood; Heart; Image segmentation; Image sequences; Muscles; Myocardium; Speckle; Statistics; Ultrasonic imaging;
Conference_Titel :
Ultrasonics Symposium, 2006. IEEE
Conference_Location :
Vancouver, BC
Print_ISBN :
1-4244-0201-8
Electronic_ISBN :
1051-0117
DOI :
10.1109/ULTSYM.2006.508