The effect of image normalization and iteration number of the linear despeckle filtering on the structural similarity criteria of the consecutive ultrasound images of the common carotid artery

Document Type : Research Paper

Authors

1 Department of radiology technology, Shahid Beheshti University of Medical Sciences;

2 Imaging Center of Imam Khomaini Hospital, Tehran University of Medical Sciences,

Abstract

The aim of the present study is to evaluate the effect of image normalization and iteration number of the linear despeckle filtering on the consecutive ultrasound image quality of the carotid artery and to select the optimum iteration number of ultrasound despeckle filtering. 750 consecutive ultrasonic images over three cardiac cycles of the common carotid artery of three healthy male volunteers (32±9Yr) and 250 consecutive ultrasonic images over three cardiac cycles of the common carotid artery of a male volunteers (65 Yr) having atherosclerotic stenosis were recorded. Using a custom-written program in MATLAb software, the images were first normalized based on gray scale level of the blood and adventitia. Then a linear despeckle filter was applied in 10 iteration to the normalized images. The quality of the images processed with different iterations were evaluated via metrics including mean, variance, signal to noise ratio, relative contrast, noise speckle index, contrast to speckle ratio and structural similarity.
Results of the present study shows that among all evaluated metrics, structural similarity is the only metric which is not monotone with iteration number so that by increasing the iteration, initially it increases and then decreases. The optimum iteration of the despeckling filter is that of the maximum structural similarity. According to the results of the present study it seems that 2 to 5 iterations of linear filtering of size 5×5 is required to obtain the maximum structural similarity and further increasing the iteration number results in image texture loss while more computational cost.

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