Classification of benign and malignant bone lesions on CT imagesusing support vector machine

A comparison of kernel functions

M. V. Suhas, Rishav Kumar

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
Externally publishedYes
Event1st IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Bangalore, India
Duration: 20-05-201621-05-2016

Conference

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

Fingerprint

Tomography
Support vector machines
Tumors
Bone
Computer aided diagnosis
Classifiers

All Science Journal Classification (ASJC) codes

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

Cite this

Suhas, M. V., & Kumar, R. (2017). Classification of benign and malignant bone lesions on CT imagesusing support vector machine: A comparison of kernel functions. In 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings (pp. 821-824). [7807941] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTEICT.2016.7807941
Suhas, M. V. ; Kumar, Rishav. / Classification of benign and malignant bone lesions on CT imagesusing support vector machine : A comparison of kernel functions. 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 821-824
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Suhas, MV & Kumar, R 2017, Classification of benign and malignant bone lesions on CT imagesusing support vector machine: A comparison of kernel functions. in 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings., 7807941, Institute of Electrical and Electronics Engineers Inc., pp. 821-824, 1st IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016, Bangalore, India, 20-05-16. https://doi.org/10.1109/RTEICT.2016.7807941

Classification of benign and malignant bone lesions on CT imagesusing support vector machine : A comparison of kernel functions. / Suhas, M. V.; Kumar, Rishav.

2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 821-824 7807941.

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

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Suhas MV, Kumar R. Classification of benign and malignant bone lesions on CT imagesusing support vector machine: A comparison of kernel functions. In 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 821-824. 7807941 https://doi.org/10.1109/RTEICT.2016.7807941