Analysis of Detection of Atherosclerosis Using Marker Controlled Watershed Modified Segmentation Altorithm

Authors:

Shiv Shankar Rai (Manav Rachna International University, Faridabad)

Shaveta Bhatia (Manav Rachna International University, Faridabad)

Keywords: Atherosclerosis, Intravascular ultrasound (IVUS), watershed algorithm and image denoising

Abstract:

Heart attack is caused due to atherosclerosisand strokes in humans. Carotid atherosclerosis, i.e. plaque build-up in the arterial wall due to the formation of proteins, cholesterol and lipids in excess is the major cause of stroke. To resolve the mechanism behind plaque formation many research institutes are investigating plaque formation, plaque growth and the factors affecting plaque in the Coronary artery. Intravascular Ultrasound Imaging (IVUS) is a new medical promising technique for coronary heart disease. This technique is expected to play a crucial role in plaque detection in coronary artery because images of better quality can be produced at video-rate and therefore it will help in analyzing moving structures. This proposed approach presented in this paper will consists of recording of ultrasound images from tissue under different degree of deformation and then various steps of preprocessing using digital image processing software (MATLAB) will be used for feature extraction, analysis and early diagnosis by removing speckle noise from the image which is the reason for corrupting images fine details.

References:

[1] Anju Bale, “An Improved Watershed Image Segmentation Technique using MATLAB” International Journal of Scientific & Engineering Research, vol. 3, 6 June 2012.

[2] Faouzi Benzarti and Hamid Amiri “Speckle Noise Reduction in Medical Ultrasound Images” International journal of computer science issues,issue 2, Vol. 9, p187, march 2012.

[3] Ahmad EL Allaoui and M’barek NASRI “ Medical Image Segmentation By Marker-Controlled Watershed And Mathematical Morphology”,the international journal of multimedia and its application, Vol. 4,No. 3, June 2012.

[4] Alka Vishwa and Shilpa Sharma,”Modified Method for Denoising the Ultrasound Images by Wavelet
Thresholding”, I.J. Intelligent Systems and Applications 6, pp 25-30, 2012.

[5] Anthony N. DeMaria, “Imaging Vulnerable Plaque by Ultrasound” ,Journal of the American College of Cardiology,Vol. 47, No. 8, 2005.

[6] Firas Wada and Mohamed Ali Hamdi, “3D Segmentation of Intravascular Ultrasound Images: A Fast-Marching Method”, Journal of Radiology and Diagnostic Imaging, vol. 1, pp 29-36, 2013.

[7] Kalpana Saini et.al, “Ultrasound Imaging and Image sSegmentation in the area of Ultrasound: A Review”, International Journal of Advanced Science and TechnologyVol. 24, November, 2010.

[8] R.Sukanesh et.al “Speckle Noise Reduction in Ultrasound Images by Wavelet Thresholding based on Weighted Variance “ International Journal of Computer Theory and Engineering, Vol. 1, No. 1, pp 1793-8201 April 2009.

[9] S.Satheesh and Dr.KVSVR Prasad, Medical Image Denoising using Adaptive Threshold Based on Contourlet Transform Advanced Computing: An International Journal ( ACIJ ), Vol.2, No.2, March 2011.

[10] Thodeti Srikanth et al, “Color Image Segmentation using Watershed Algorithm” , (IJCSIT) International Journal of Computer Science and Information technologies, vol. 2 (5), pp 2332-2334, 2011.