Ünal, YavuzKoçer, Hasan ErdinçAkkurt, Halil Ekrem2020-03-262020-03-2620119.78161E+12https://dx.doi.org/10.1109/INISTA.2011.5946147https://hdl.handle.net/20.500.12395/27155TUBITAK;IEEE2011 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2011 -- 15 June 2011 through 18 June 2011 -- Istanbul-Kadikoy -- 85879The reduction of fluid that acts as shock absorber placed in lumbar intervertebral discs causes pains and this case is named as degenerative disc disease. Magentic Resonance Imaging is generally used for diagnosis of this disease by radiologists or doctors. However, due to personal errors such as fatigue, inexperience, oversight, wrong diagnosis is possible. In order to prevent these, computer-aided diagnostic (CAD) methods are mostly preferred. In this work, the performance of two different feature extraction methods is compared. The saggital MR images taken from 9 patients were feature extracted by using grey level co-occurrence matrix (GLCM) and average absolute deviation (AAD) methods. The obtained feature vectors were classified by using multi-layered perceptron (MLP) artificial neural networks. © 2011 IEEE.en10.1109/INISTA.2011.5946147info:eu-repo/semantics/closedAccessartificial neural networksaverage absolute deviationgrey level co-occurrence matrixintervertebral degenerative disk diseaseConference Object490494N/A