Automated Screening of Fetal Heart Chambers from 2-D Ultrasound Cine-Loop Sequences

Automated Screening of Fetal Heart Chambers from 2-D Ultrasound Cine-Loop Sequences

N. Sriraam (Department of Medical Electronics, M.S Ramaiah Institute of Technology, Bangalore, Karnataka, India), S.Vijayalakshmi (Department of Biomedical Engineering, Rajalakshmi Engineering College, Chennai, India & Trivitron Medical Systems, Chennai, Tamil Nadu, India) and S.Suresh (Mediscans Pvt Ltd, Chennai, Tamil Nadu, India)
Copyright: © 2012 |Pages: 10
DOI: 10.4018/ijbce.2012070103
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Abstract

Fetal cardiac ultrasonic imaging technique has become increasingly popular in the recent years for the detection of fetal congenital abnormalities at an early stage. Due to the low signal-to-noise ratio of the ultrasound imaging, the automatic detection methods should incorporate suitable preprocessing filtering techniques to enhance the segmentation techniques efficiently. This paper suggests the application of median and morphological filtering operation for removing speckle noise. Then the four heart chambers are segmented independently based on the shape priors. The amorphous snake’s helps in identifying the contours of the chamber edges individually based on shape pattern. Experimental study involves the ultrasound cine-loop sequences of the apical four chamber view of fetal heart with a constant frame rate of 25 frames per second (fps) with varying duration of 10-30s encompassing a range of 20-40 complete cardiac cycles. The simulation result confirms the suitability of proposed scheme for automated screening of fetal heart chambers.
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Introduction

Congenital heart defects happen because of incomplete or abnormal development of the fetus' heart during the very early weeks of pregnancy. Some are known to be associated with genetic disorders, such as Down syndrome, but the cause of most congenital heart defects is unknown. The major congenital heart diseases have characteristic abnormalities seen in the fetal ultrasound images taken at different trimesters of pregnancy. The sweep technique involves sweeping the transducer beam in a transverse plane from the level of the four-chamber view towards the fetal neck. By doing so, the outflow tract vessels are observed. The sweep consists of the following views: four-chamber view, five-chamber view, main pulmonary artery or 3-vessel view, and the tracheal view. In a fetal heart examination using ultrasound, the abdominal view, the four-chamber view and both (left and right) cardiac outflow tracts should be obtained at screening level (Achiron et al., 1992). Additional fetal cardiac views are crucial for the sequential segmental analysis to assess the connections and anatomical detail (Jantarasaengaram, 2010).

The diagnosis of fetal heart requires highly skilled operations and is often time-consuming for doctors (Siqueria et al., 2005). From this point of view, the state-of-the-art technology in fetal cardiac ultrasound examination is that computerized methods are proposed and they are trying to assist the doctors in the diagnosis of anomalies in fetal heart. The present scenario is that the fetal cardiac images have been evaluated manually. This might usually lead to human error during observation. This can be overcome by using image processing algorithms to set a standard to evaluate the images automatically. This can result in more appropriate interpretation of the images. A conventional 2-dimensional [2D] ultrasound transducer without position sensing, freehand acquisition using a conventional 2D ultrasound transducer with position sensing, and automated acquisition using dedicated mechanical volume probes) rely on the acquisition of a series of 2D frames that are then reassembled by the ultrasound equipment and displayed as a 3D volume data set (Pretorius et al., 2001). Two dimensional ultrasound methods have traditionally relied on both static and real-time imaging to understand fetal cardiac anatomy and function (Belohlavek et al., 1993)

Vibhakar Shrimali et al (2009) carried out a cross-sectional study on fetal ultrasound images that were processed using morphological operators to obtain the shape of the femur. In Zayed et al (2001) fuzzy based clustering algorithm is applied for grouping together those pixels in the image, which have similar features in the feature space. Lassige et al (2000) used the level set algorithm to detect the septal defects. Siqueira et al [3] proposed to apply the self-organizing map to segment the fetal heart and obtain the heart structure. These computerized methods are mainly based on the information of edge or region, which is not reliable for the ultrasound data of early trimester fetal heart (Deng et al., 2007)

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