Machine learning in the detection of dental cyst, tumor, and abscess lesions.

Background And Objective: Dental panoramic radiographs are utilized in computer-aided image analysis, which detects abnormal tissue masses by analyzing the produced image capacity to recognize patterns of intensity fluctuations. This is done to reduce the need for invasive biopsies for arriving to a diagnosis. The aim of the current study was to examine and compare the accuracy of several texture analysis techniques, such as Grey Level Run Length Matrix (GLRLM), Grey Level Co-occurrence Matrix (GLCM), and wavelet analysis in recognizing dental cyst, tumor, and abscess lesions.

Assessment of periodontal status among dental fluorosis subjects using community periodontal index of treatment needs.

Aim: To determine the periodontal status and treatment needs among dental fluorosis subjects residing in Ennore, Chennai, using Community Periodontal Index of Treatment Needs (CPITN).

Materials And Methods: All the subjects with dental fluorosis above 15 years of age, permanent residents of Ennore, were included in the study. Subjects with known systemic diseases and subjects with other intrinsic dental stains were excluded from the study.