Caries Detection with the Aid of Multilinear Principal Component Analysis and Neural Network

Diagnosis of tooth caries or cavities are regarded as one of the promising research issues for the past two decades. Moreover, several techniques are established to diagnose the tooth demineralization, tooth decaying and re-mineralization. However, the complexity of tooth decaying diagnosis emerges when the surroundings are comparatively multifaceted. Hence, for solving such issues, this paper establishes caries diagnosing model. Here, the feature selection is dependent on Multilinear Principal Component Analysis (MPCA). In addition, the classification is performed by exploiting well-known classifier known as Neural Network (NN).