Analysis of Dental Images using Artificial Immune Systems

Abstract

Abstract-This paper introduces a preliminary effort to develop an automatic image analysis method using Artificial Immune Systems for clinical dental diagnosis. To diagnose dental deformity, especially malocclusion, manual measurement of certain geometry on the X-ray images is traditionally used, which relies on subjective judgment to determine the reference points. This paper proposes a feature extraction method that is based on the brightness distribution of the image instead of the anatomical parts. A negative selection algorithm is then applied to the data represented as real-valued vectors to detect the cases of severe malocclusion. Using the same data representation, oneclass SVM was also tried to compare the detection capability with the negative selection algorithm. The results show that the negative selection algorithm appears more suitable for this problem.