Segmentation of the heart muscle in 3-D pediatric echocardiographic images.
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SourceUltrasound in Medicine and Biology, 33, 9, (2007), pp. 1453-62
Article / Letter to editor
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Paediatrics - OUD tm 2017
Ultrasound in Medicine and Biology
SubjectCTR 1: Functional imaging; IGMD 1: Functional imaging; IGMD 5: Health aging / healthy living; NCEBP 14: Cardiovascular diseases; ONCOL 5: Aetiology, screening and detection; UMCN 1.1: Functional Imaging; UMCN 2.1: Heart, lung and circulation
This study aimed to show segmentation of the heart muscle in pediatric echocardiographic images as a preprocessing step for tissue analysis. Transthoracic image sequences (2-D and 3-D volume data, both derived in radiofrequency format, directly after beam forming) were registered in real time from four healthy children over three heart cycles. Three preprocessing methods, based on adaptive filtering, were used to reduce the speckle noise for optimizing the distinction between blood and myocardium, while preserving the sharpness of edges between anatomical structures. The filtering kernel size was linked to the local speckle size and the speckle noise characteristics were considered to define the optimal filter in one of the methods. The filtered 2-D images were thresholded automatically as a first step of segmentation of the endocardial wall. The final segmentation step was achieved by applying a deformable contour algorithm. This segmentation of each 2-D image of the 3-D+time (i.e., 4-D) datasets was related to that of the neighboring images in both time and space. By thus incorporating spatial and temporal information of 3-D ultrasound image sequences, an automated method using image statistics was developed to perform 3-D segmentation of the heart muscle.
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