Significance of haralick features in bone tumor classification using support vector machine

M. V. Suhas, B. P. Swathi

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Accurate classification of bone lesions into benign and malignant tumors plays a key role in determining the treatment course (surgical intervention or radiation), an essential part of radiologists work. In this work, we investigate the significance of Haralick textural feature components in an application to computer-aided classification of the bone tumor into benign and malignant. The Haralick features from Computed Tomography (CT) images are extracted to form the dataset. Support Vector Machine (SVM) with medium Gaussian kernel function is trained and tested with the dataset consisting of various malignant and benign tumors. The dataset prepared by extracting the Haralick features are subjected to Correlation-Based Feature Subset (CFS) Selection. The accuracy of the classifier is measured in each case. The study reveals an increased accuracy post-feature selection.

Original languageEnglish
Title of host publicationLecture Notes in Electrical Engineering
PublisherSpringer Verlag
Pages349-361
Number of pages13
DOIs
Publication statusPublished - 01-01-2019
Externally publishedYes

Publication series

NameLecture Notes in Electrical Engineering
Volume478
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Fingerprint

Support vector machines
Tumors
Bone
Tomography
Feature extraction
Classifiers
Radiation

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

Cite this

Suhas, M. V., & Swathi, B. P. (2019). Significance of haralick features in bone tumor classification using support vector machine. In Lecture Notes in Electrical Engineering (pp. 349-361). (Lecture Notes in Electrical Engineering; Vol. 478). Springer Verlag. https://doi.org/10.1007/978-981-13-1642-5_32
Suhas, M. V. ; Swathi, B. P. / Significance of haralick features in bone tumor classification using support vector machine. Lecture Notes in Electrical Engineering. Springer Verlag, 2019. pp. 349-361 (Lecture Notes in Electrical Engineering).
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Suhas, MV & Swathi, BP 2019, Significance of haralick features in bone tumor classification using support vector machine. in Lecture Notes in Electrical Engineering. Lecture Notes in Electrical Engineering, vol. 478, Springer Verlag, pp. 349-361. https://doi.org/10.1007/978-981-13-1642-5_32

Significance of haralick features in bone tumor classification using support vector machine. / Suhas, M. V.; Swathi, B. P.

Lecture Notes in Electrical Engineering. Springer Verlag, 2019. p. 349-361 (Lecture Notes in Electrical Engineering; Vol. 478).

Research output: Chapter in Book/Report/Conference proceedingChapter

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Suhas MV, Swathi BP. Significance of haralick features in bone tumor classification using support vector machine. In Lecture Notes in Electrical Engineering. Springer Verlag. 2019. p. 349-361. (Lecture Notes in Electrical Engineering). https://doi.org/10.1007/978-981-13-1642-5_32