ProgramsView all programs
From the news
- Chancellor Amma Addresses the Parliament of World’s Religions
- Amrita Students Qualify for the European Mars Rover Challenge
Publication Type : Conference Proceedings
Publisher : Advances in Intelligent Systems and Computing
Source : Advances in Intelligent Systems and Computing, Volume 195 AISC, p.611-624 (2013)
Campus : Coimbatore
School : School of Engineering
Center : Center for Computational Engineering and Networking
Department : Computer Science
Verified : Yes
Year : 2013
Abstract : Ultrasound imaging is considered to be one of the most cost-effective and non-invasive techniques for conclusive diagnosis in some cases and preliminary diagnosis in others. Automatic liver tissue characterization and classification from ultrasonic scans have been for long, the concern of many researchers, and has been made possible today by the availability of the most powerful and cost effective computing facilities. Automatic diagnosis and classification systems are used both for quick and accurate diagnosis and as a second opinion tool for clarifications. This paper analyzes the effect of various linear, non linear and diffusion filters in improving the quality of the liver ultrasound images before proceeding to the subsequent phases of feature extraction and classification using Gray Level Run Length Matrix Features and Support Vector Machines respectively.
Cite this Research Publication : K. Raghesh Krishnan and Sudhakar, R., “Automatic Classification of Liver Diseases from Ultrasound Images Using GLRLM Texture Features”, Advances in Intelligent Systems and Computing, vol. 195 AISC. pp. 611-624, 2013.