Texture Analysis of Mandibular Trabecular Bone in Correlation with Age and Gender Using Cone Beam CT Images: A Cross-Sectional Study

Abstract Background: Texture analysis of medical images plays a significant role in extracting quantitative features that cannot be assessed visually. Objective: To compare gray-level co-occurrence matrix (GLCM) texture features of mandibular trabecular bone in different age-gender groups using CBCT images. Methods: In this retrospective cross-sectional study, 120 mandibular CBCT scans of adult male and female patients were recruited. The study sample was divided into four different age-gender groups. Texture analysis was performed using MaZda software, and 11 GLCM texture features were extracted. Results: Angular second moment, entropy, correlation, inverse different moment, sum of average, difference of entropy, and sum of entropy showed statistically significant differences between age-gender groups. Conclusion: The results of this study concluded that principal texture features of mandibular trabecular bone were found to differentiate between different age-gender groups.