title: Texture based feature extraction methods for content based medical image retrieval systems.
abstract: The developments of content based image retrieval (CBIR) systems used for image archiving are continued and one of the important research topics. Although some studies have been presented general image achieving, proposed CBIR systems for archiving of medical images are not very efficient. In presented study, it is examined the retrieval efficiency rate of spatial methods used for feature extraction for medical image retrieval systems. The investigated algorithms in this study depend on gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), and Gabor wavelet accepted as spatial methods. In the experiments, the database is built including hundreds of medical images such as brain, lung, sinus, and bone. The results obtained in this study shows that queries based on statistics obtained from GLCM are satisfied. However, it is observed that Gabor Wavelet has been the most effective and accurate method.
authors.affiliation: Department of Computer Engineering, Faculty of Engineering, Fırat University, 23119, Elazig, Turkey.
authors.forename: Burhan
authors.initials: B
authors.lastname: Ergen
authors.affiliation: Department of Software Engineering, Faculty of Technology, Fırat University, 23119, Elazig, Turkey.
authors.forename: Muhammet
authors.initials: M
authors.lastname: Baykara
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D057225:Data Mining / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011873:Radiology Information Systems / Q000458:organization & administration*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D058067:Wavelet Analysis
keywords: Content-based image retrieval; GLCM; GLRLM; Gabor wavelet