Automated detection of dental diseases using image processing

Abstract

The computer aided diagnostic system for dental diseases is developed for maintaining the database of the patient automation of the diagnostic measurements diagnosing the health issues and conditions The quality of diagnosis is improved by the development of modern diagnostic tools using several image processing based segmentation detection and diagnosis methods The dental x ray image analysis gives the information about the early detection of dental caries dental cyst and dental plaque in dentistry to provide lifetime care The automation of diagnostic imaging is desired in the field of dentistry due to increasing demands for dental healthcare This diagnosis process takes much time even for a single patient and generates variation in the diagnosis among dental and medical scientists To avoid that complication many kinds of research are going on in the area of the automation of diagnostic system The Dental X ray gives pictures of teeth parts bones and other surrounding areas So that the Dental X ray images can be utilised for the detection of decayed tooth region detection of any inflammation due to infection on the oral cavity in the teeth The automated detection of dental caries plaque and the cyst boundary is an important step for diagnosis planning and treatment of the dental diseases The robust and efficient algorithms for proper segmentation of dental x ray images are very hard to find The automatic or semi automatic lesion segmentation and detection is a challenging problem in dental research to eliminate the misjudgments in lesion and non lesion area diagnosis Even though many medical image segmentation methods have been proposed in the past several years due to differences in the image and modality used still it is a complex and challenging one Therefore the selection of an appropriate algorithm can be a difficult dilemma to a segmentation problem The advanced segmentation method may work well on one problem and may not work on another problem Therefore it is a very tedious one to develop the image segme