Open AccessCLASSIFICATION OF OSTEOPOROSIS BASED ON TEXTURE FEATURES
Author(s) -
P. Prabakaran,
G Manikannan,
T. G. Vijayalakshmi
Publication year - 2019
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2019.v04i08.036
Subject(s) - texture (cosmology) , artificial intelligence , osteoporosis , computer science , pattern recognition (psychology) , medicine , image (mathematics) , pathology
There was substantial challenge in assessment of osteoporotic disease from the radiograph image. Texture characteristics are visually very analogous when witnessed from the naked eye for the bone microarchitecture of the osteoporotic and healthy cases which will be a challenging grouping problem. An approach that is based on a combination of multi resolution Gabor filters and 1D local binary pattern (1DLBP) features is proposed to extract the discriminative patterns in all the orientations and scales simultaneously. Gabor filter are used due to their advantages in yielding a scale and orientation sensitive analysis whereas LBPs are useful for quantifying microstructural changes in the images. The proposed method shows good classification results with an overall accuracy of about 72.71%.