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Comparison of Edge Detection Algorithms in the Framework of Despeckling Carotid Ultrasound Images Based on Bayesian Estimation Approach

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Computer Vision, Pattern Recognition, Image Processing, and Graphics (NCVPRIPG 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 841))

Abstract

Common carotid artery (CCA) ultrasound with estimation of Intima Media Thickness (IMT) is the safe and non-invasive technique for predicting the cardiovascular risks. The precise quantification of IMT is useful for evaluating the risk of cardiovascular disease. The presence of speckle noise in carotid ultrasound image reduces the quality of the image and automatic human interpretation. Carotid ultrasound images have multiplicative speckle noise and it is difficult remove compared to the additive noises. The speckle removal filters have a greater restriction in edges and characteristics preservation. In this paper, we propose an extension of our earlier work with a fully automated Region of Interest (ROI) extraction and speckle denoising using optimized bayesian least square estimation (BLSE) approach followed by edge detection. The objective of the paper is to reduce the speckle noise in the extracted ROI of carotid ultrasound images using state-of-art denoising techniques and then followed by edge detection techniques and compared them with the edges extracted by these edge operators of ground truth image. The proposed algorithm experiments with 50 B-mode carotid ultrasound images. Experimental analysis shows that proposed method achieves better results as compared to other edge detection methods in terms of structural similarity Index Map (SSIM), correlation of coefficient (CoC), peak signal to noise ratio (PSNR) and mean square error (MSE) measures. Based on results, proposed work more effective in terms of visual inspection and detail preservation in carotid ultrasound images.

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Acknowledgement

The authors would like to thank Department of Radiology, Father Muller Hospital, Mangalore for valuable contribution in collecting B-mode longitudinal ultrasound images of the patients.

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Authors and Affiliations

  1. National Institute of Technology Karnataka, Surathkal, India

    Y. Nagaraj & A. V. Narasimhadhan

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  1. Y. Nagaraj
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  2. A. V. Narasimhadhan
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Correspondence to Y. Nagaraj .

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Editors and Affiliations

  1. Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India

    Renu Rameshan

  2. Indraprastha Institute of Information Technology, New Delhi, India

    Chetan Arora

  3. Indian Institute of Technology, New Delhi, India

    Sumantra Dutta Roy

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Nagaraj, Y., Narasimhadhan, A.V. (2018). Comparison of Edge Detection Algorithms in the Framework of Despeckling Carotid Ultrasound Images Based on Bayesian Estimation Approach. In: Rameshan, R., Arora, C., Dutta Roy, S. (eds) Computer Vision, Pattern Recognition, Image Processing, and Graphics. NCVPRIPG 2017. Communications in Computer and Information Science, vol 841. Springer, Singapore. https://doi.org/10.1007/978-981-13-0020-2_37

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  • DOI: https://doi.org/10.1007/978-981-13-0020-2_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0019-6

  • Online ISBN: 978-981-13-0020-2

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