Skip to main navigation Skip to search Skip to main content

Classification of benign and malignant bone lesions on CT imagesusing support vector machine: A comparison of kernel functions

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Skeletal metastasis has tendency to develop from any kind of primary tumor. In the spine, the vertebral body is the most common site of metastasis which then extends to pedicle. About 2/3rd of the malignant tumor cases are found to develop metastasis. This work presents a Computer Aided Diagnosis (CAD) system that helps radiologists in differentiating malignant and benign bone lesions in the spine on Computed Tomography (CT) images usingSupport Vector Machines(SVM).The CT images are segmented using Snakes or Active Contour Model to retrieve the Region of Interest(ROI). From the segmented images, Haralick features are calculated. These features are then passed to the SVM classifier. With the help of SVM model generated, the data are classified into benign and malignant nodules. The performances of different kernel functions are compared.

    Original languageEnglish
    Title of host publication2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages821-824
    Number of pages4
    ISBN (Electronic)9781509007745
    DOIs
    Publication statusPublished - 05-01-2017
    Event1st IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Bangalore, India
    Duration: 20-05-201621-05-2016

    Publication series

    Name2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings

    Conference

    Conference1st IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016
    Country/TerritoryIndia
    CityBangalore
    Period20-05-1621-05-16

    All Science Journal Classification (ASJC) codes

    • Computer Networks and Communications
    • Computer Science Applications
    • Information Systems
    • Electrical and Electronic Engineering

    Fingerprint

    Dive into the research topics of 'Classification of benign and malignant bone lesions on CT imagesusing support vector machine: A comparison of kernel functions'. Together they form a unique fingerprint.

    Cite this