SQL based cardiovascular ultrasound image classification

Authors:
S. Nandagopalan;Adiga B. Suryanarayana;T. S. B. Sudarshan;Dhanalakshmi Chandrashekar;C. N. Manjunath
Affiliations:
Department of Computer Science and Engineering, Amrita Vishwa Vidyapeetham, Amrita School of Engineering, Bangalore 560 004, India;Tata Consultancy Services, Bangalore 560 066, India;Department of Computer Science and Engineering, Amrita Vishwa Vidyapeetham, Amrita School of Engineering, Bangalore 560 035, India;Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bangalore 560 069, India;Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bangalore 560 069, India
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2013

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Abstract

This paper proposes a novel method to analyze and classify the cardiovascular ultrasound echocardiographic images using Naïve-Bayesian model via database OLAP-SQL. Efficient data mining algorithms based on tightly-coupled model is used to extract features. Three algorithms are proposed for classification namely Naïve-Bayesian Classifier for Discrete variables NBCD with SQL, NBCD with OLAP-SQL, and Naïve-Bayesian Classifier for Continuous variables NBCC using OLAP-SQL. The proposed model is trained with 207 patient images containing normal and abnormal categories. Out of the three proposed algorithms, a high classification accuracy of 96.59% was achieved from NBCC which is better than the earlier methods.