Noise Reduction and Segmentation of Common Carotid Artery in Ultrasound Images and Measurement of Intima Media Thickness
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2018 by IJETT Journal|
|Year of Publication : 2018|
|Authors : Ishani Mishra, Abhijnan Mitra, Gaurav Kumar Gupta , Mohammed Asif
|DOI : 10.14445/22315381/IJETT-V59P205|
Ishani Mishra, Abhijnan Mitra, Gaurav Kumar Gupta , Mohammed Asif"Noise Reduction and Segmentation of Common Carotid Artery in Ultrasound Images and Measurement of Intima Media Thickness", International Journal of Engineering Trends and Technology (IJETT), V59(1),30-36 May 2018. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
The study is about the assessment of use of filters for noise reduction in ultrasound images of the common carotid artery (CCA) using intima–media thickness(IMT). IMT is a risk-free technique for examining subclinical atherosclerosis and cardiovascular risk. A new combined speckle reducing anisotropic diffusion (SRAD) filter for noise reduction is then proposed. Initially samples of ultrasound images of carotid arteries were collected. The program was implemented using MATLAB software to extract consecutive images in bit map format. In addition to that, another program was implemented in MATLAB to apply the region of interest (ROI) to the thickness of the intima–media of the posterior walls of the arteries. Variety of noise reduction filters and Canny edge detection were implemented separately in the ROI. The program measured mean square error (MSE) and peak signal-to-noise ratio(PSNR). Results implied that the new combined SRAD filter with Canny edge detection generated minimum value for MSE and the maximum value for PSNR. This indicates that the results, both MSE and PSNR were better detected by the proposed SRAD filter with Canny edge detection, than it did for the other filters for speckle suppression and preservation detail in carotid arteries ultrasound images. Ultrasound images of carotid artery are one of the parts that hard to identify by inexperience doctor or radiologist because the shape is almost same like the muscle layer. Hence, the segmentation of carotid artery layer and measurement of the Intima Media Thickness (IMT) is proposed. We use Otsu’s thresholding algorithm to segment the carotid artery from the background. After applying binarization technique and by performing morphological operations, the carotid artery region in the image is clearly visible, such that it is easy to measure the Intima Media Thickness (IMT).
1. Rafati, M., Arabfard, M., Rafati Rahimzadeh, M.: ‘Comparison of different edge detections and noise reduction on ultrasound images of carotid and brachial arteries using a speckle reducing anisotropic diffusion filter’, Iran. Red Crescent Med. J., 2014, 16, (9),
2. Hafizah, W.M., Supriyanto, E.: ‘Comparative evaluation of ultrasound kidney image enhancement techniques’, Int. J. Comput. Technol. Appl., 2011, 21, International Journal of Engineering Trends and Technology (IJETT) – Volume 59 Issue 1- May 2018 ISSN: 2231-5381 http://www.ijettjournal.org Page 36
3. Benes, R., Riha, K.: ‘Medical image denoising by improved Kuan filter’, Adv. Electr. Electron. Eng., 2012, 10..
4. Kaur, J., Kaur, J., Kaur, M.: ‘Survey of despeckling techniques for medical ultrasound images’, Int. J. Comput. Technol. Appl., 2011, 2, pp. 1003–1007.
5. Kaur, J., Kaur, J., Kaur, M.: ‘Survey of despeckling techniques for medical ultrasound images’, Int. J. Comput. Technol. Appl., 2011, 2, pp. 1003–1007
6. Om, H., Biswas, M.: ‘A new image denoising scheme using soft-thresholding’, J. Signal Inf. Process., 2012, 3, pp. 360–363
7. Sudha, S., Suresh, G.R., Sukanesh, R.: ‘Speckle noise reduction in ultrasound images by wavelet thresholding based on weighted variance’, Int. J. Comput. Theory Eng., 2009, 1, pp. 7–12
8. Nicolae, M.C., Moraru, L., Onose, L.: ‘Comparative approach for speckle reduction in medical ultrasound images’, Rom. J. Biophys., 2009, 1, pp. 13–21
9. Vishwa, A., Sharma, S.: ‘Speckle noise reduction in ultrasound images by wavelet thresholding’, Int. J. Adv. Res. Comput. Sci. Softw. Eng., 2012, 2, pp. 25–30
10. Yu, J., Wang, Y., Shen, Y.: ‘Noise reduction and edge detection via kernel anisotropic diffusion’, Pattern Recognit. Lett., 2008, 29, pp. 1496–1503
11. Geethalkshmi, S.N., Suguna, J.: ‘Hybrid models for denoising ultrasonic images’, J. Glob. Res. Comput. Sci., 2010, 1, pp. 38–45
12. Shruthi, G., Usha, B.S., Sandya, S.: ‘A novel approach for speckle reduction and enhancement of ultrasound images’, Int. J. Comput. Appl., 2012, 45, pp. 14–20
13. Acharjya, P.P., Das, R., Ghoshal, D.: ‘Study and comparison of different edge detectors for image segmentation’, Glob. J. Comput. Sci. Technol. Graph. Vis., 2012, 12, pp. 29–32
14. Preetha, J., Selvarajan, S., Suresh, P.: ‘Comparative analysis of various image edge detection techniques for two dimensional CT scan neck disc image’, Int. J. Comput. Sci. Commun., 2012, 3, pp. 57–61
15. Singh, R., Kaur, A.: ‘Comparative analysis of speckle noise reduction techniques and their affect on image edge localization’, Int. J. Comput. Sci. Technol., 2011, 2, pp. 78–82
16. Hajiaboli, M.N.: ‘An anisotropic fourth-order diffusion filter for image noise removal’, Int. J. Comput. Vis., 2011, 92, pp. 177–191.
CCA, IMT, SRAD, Canny Edge Detection, ROI, MSE, PSNR, Otsu's Thresholding