Improved segmentation of echocardiographic images using fusion of images from different cardiac cycles

Abstract

In this work, an algorithm for the detection of the left ventricular border in two-dimensional long axis echocardiographic images is presented. In its preprocessing stage, images fusion was applied to a sequence of images composed of three cardiac cycles. This method exploits the similarity of corresponding frames from different cycles and produces contrast enhancement in the left ventricular boundary. This result improves the performance of the segmentation stage which is based on watershed transformation. The obtained left ventricle border is quantitatively and qualitatively compared with contours manually segmented by a cardiologist, and with results obtained using seven different techniques from the literature.

Postprocessing Approaches for the Improvement of Cardiac Ultrasound B-Mode Images: A Review

“…The results were promising with images from ten cardiac cycles providing a good tradeoff between noise suppression and processing resources. Similar approaches have in recent studies been adopted and combined with compounding of temporally adjacent frames as a preprocessing step for more effective image segmentation of cardiac structures [110], [111]. However, these studies [109]- [111] suffered from two major limitations.…”

“…4 and 5). The potential of the approach has also been recognized by a number of studies [110], [111], [116], [117], even for other imaging modalities such as CT [118]. However, while the accurate and robust spatio-temporal image alignment is a key process for effective compounding of data from consecutive cardiac cycles, many current implementations fail to provide a reliable and effective registration approach.…”

Cavity Segmentation and Stroke Volume Measurement Methods From Echocardiographic Images: Review

“…Kondo et al (1995) used frame-by-frame subtraction to indicate the motion in their assessment of the delayed onset of the LV, where 60 frames/sec echocardiographic images were used. Amorim et al (2009) used fused three frames in equivalent positions of three cardiac cycles as the first step of pre-processing to enhance LV wall construction and for noise reduction. Then, smoothing and thresholding were applied to improve the segmentation performance.…”

Dynamic Enhancement of B-Mode Cardiac Ultrasound Image Sequences

“…There are studies that have employed spatial compounding through transducer repositioning for the enhancement of 3-D cardiac ultrasound data (Gooding et al 2010;Mulder et al 2014;Rajpoot et al 2011;Szmigielski et al 2010;Yao et al 2010). Some studies have attempted to enhance 2-D cardiac ultrasound images by averaging temporally consecutive frames (Achmad et al 2009;dos Reis et al 2009;Li et al 1994;Petrovic et al 1986). Other studies have utilised the repeated rhythmic contractions of the heart to acquire and compound multiple partially decorrelated 2-D images of the same cardiac phase over consecutive cardiac cycles through a single acoustic window.…”

“…Other studies have utilised the repeated rhythmic contractions of the heart to acquire and compound multiple partially decorrelated 2-D images of the same cardiac phase over consecutive cardiac cycles through a single acoustic window. The process has been referred to as temporal compounding (Abiko et al 1997;Amorim et al 2009;Klingler et al 1989;Olstad 2002;Perperidis et al 2009;Rigney and Wei 1988;Unser et al 1989;van Ocken et al 1981;Vitale et al 1993).…”