Osteoporosis detection by using CT images based on Gray Level Co-occurrence Matrix and Rule based approach

Osteoporosis detection by using CT images based on Gray Level Co-occurrence Matrix and Rule based approach
Author(s):
Maya Deoker, S.N.PATIL
Keywords:
Osteoporosis, GLCM, SVM classifier.
Abstract
:Image processing is an area of active research in which medical image processing is a highly challenging field. Medical imaging techniques are being used to image the inner portions of the human body for medical diagnosis. In this paper, Gray Level Co-occurrence Matrix (GLCM) features areeffectively utilized for osteoporosis diagnosis. Early diagnosis of osteoporosis is important toprotect bone loss. The proposed system uses four GLCM features such as Contrast,Correlation, Energy, and Homogeneity for the diagnosis. The classification of osteoporotic images into normal or abnormal is obtained by the Support Vector Machine (SVM) classifier. An internal database of images is utilized for the performance analysis. The results show that the proposed approach helps the doctors to make their decision very accurately. The system provides 93% classification accuracy.
Article Details
Unique Paper ID: 145071 Publication Volume & Issue: Volume 4, Issue 7 Page(s): 377 - 381
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