Automated technique for carotid plaque characterisation and classification using RDWT in ultrasound images

ABSTRACT

In this manuscript, a novel method of rational-dilation wavelet transform (RDWT) is proposed for carotid plaque characterisation and classification in Ultrasound images. RDWT is mainly utilised for image acquisition, pre-processing, feature extraction and ensemble classification in automated plaque classification. Here, the transition bands are constructed from the transition function. The statistical features, viz mean, standard deviation, skewness, Renyi entropy, energy are extracted from the sub-bands of RDWT. The Salp Swarm Algorithm (SSA) is mainly used for selecting the optimum features. In this for selecting optimum features using SSA algorithm two conditions are satisfied such as, in the first approach, mean, standard deviation, skewness are selected and then utilised for converting the continual version of salp swarm algorithm to binary. Subsequently, the crossover operator is utilised to select the Renyi entropy, energy features including transfer functions for replacing the average operator and enhancing the characteristics of research method. Plaque Classification uses K Nearest Neighbour (KNN), Probabilistic Neural Network (PNN) and Support Vector Machine (SVM) classifiers. Experimental outcomes show the efficiency of the proposed method depending on accuracy, specificity and sensitivity. The proposed method attains accuracy of 93%, sensitivity of 90% and specificity of 94% when likened to the existing techniques, such as KNN, PNN and SVM.

KEYWORDS:

• Rational-dilation wavelet transform (RDWT)
• plaque characterisation
• classification
• Salp Swarm Algorithm (SSA)

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Arun Mailerum Perumal

Dr. M. Arun, Associate Professor, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology (Deemed to be University), Chennai.

G.N. Balaji

Dr. G. N. Balaji, is an Associate Professor from Department of Computer Science and Engineering, SRM TRP Engineering College, Trichy. He earlier worked as an Assistant Professor in Department of IT, CVR college of Engineering, Hyderabad. He graduated from Annamalai University and post-graduated with M.Tech (Computer Science Engineering) from SRM University. He completed his doctoral research in the Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University under the guidance of Dr. T. S. Subashini and his area of research is Medical Image Analysis. He published his papers in 30 international journals and conferences including Springer, Elsevier, and Taylor & Francis. He coordinated a UGC funded research project Computer Aided Detection and Diagnosis of Diaphyseal Femur Fracture. He is an active editorial member in Austin Cardiology Journal, USA, and also in professional bodies like IEEE, ACM, IAENG, ISTE and EAI. His research interest includes Image Processing, Pattern Recognition and Computer Vision. He has organized two National Workshop and faculty development programs. He is regularly invited to deliver lectures in various programs for imparting skills in research methodology to students.

J. Dhiviya Rose

Mrs. J. Dhiviya Rose received B.Tech degree in CSE from St.Xavier’s Catholic College of Engineering, Nagercoil which was then affiliated to Manonmanium Sundaranar University, Tirunelveli (Tamil Nadu, India) in 2003 and M.Tech. Degree in CSE from Karunya University, Coimbatore (Tamil Nadu, India) in 2010. She is currently working toward the Ph.D. degree at the Department of Computer Science Engineering, Uttarakhand Technical University, Dehradun (Uttarakhand, India). Her research interests are in networking, multi-agent systems, artificial intelligence and web technology.

Asha Kulkarni

Asha kulkarni received BE degree in ECE from SLN college of Engineering, Raichur, affiliated to Gulbarga University, Gulbarga, Karnataka in 1990. MTech Degree in VLSI&ES from SJCE , Mysore, Karnataka in 2008 . She is currently working toward the PhD degree at the Department of Electrical Engineering, VTU, Belagavi, Karnataka. Her research interest includes VLSI and Medical Electronics. Presently working as Head of Department of ECE at JSS Polytechnic,Mysore, Karnataka, since 1997.

Francis H Shajin

Mr. Francis H Shajin graduated from Anna University, India. He has more than 7 years of IT experience. His current research interests include very-large-scale integration, soft computing, image processing, machine learning and networking.