Early Detection of Dental Plaque Using Convolution Neural Networks: A Technological Approach for Oral Health Improvement

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@article{1705244,
      author = {Anjali Singh, Mithlesh Vishwakarma, Srishti Dubey},
      title = {Early Detection of Dental Plaque Using Convolution Neural Networks: A Technological Approach for Oral Health Improvement},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {7},
      number = {5},
      pages = {185-191},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1705244.pdf},
      abstract = {Nowadays dental or oral diseases are very common diseases and there?s half of the world's population suffers from it because of several reasons like illiteracy rate, unhygienic or poverty, etc. They are most commonly seen in age groups of 5-6, 12, and 35-41 years. Therefore, to reduce the risk factor for oral disease it?s important to have control over it at an early stage. The World Health Organization (WHO) had performed a survey to determinethepresenceoforaldiseaseandover6%of the population is facing problems related to it. In today?s century there is different technology available like Deep Learning, Machine Learning and Artificial intelligence (AI)these human technologies are nowaday, a helping hand in medical science fields because of these algorithms, treatment and detection of not only oral diseases but any kind of disease can be done efficiently. However, in this paper to detect dental plaque we have used different natural photos collected by the clinics and by applying a convolution neural network we have classified it into cavity or non-cavity. Thus, this study uses the Convolution Neural Network (CNN) algorithm, this mode requires very little Pte-process data compared to the deep learning algorithm. This paper documents the extensive datasets of dental plaque gathered from different sources and the training, testing, and Validation procedure of the detector. An important part of thistrainingisthedetectionandlocalizationofdentalbacterialplaque(DBP),whichisthemaincause of the most common oral diseases (caries and periodontal disease).The result of all the process will come that we can easily detect dental plaque with the help of this algorithm and show its accuracy. This paper attempts to review the current body of evidence regarding the role of dental plaque.},
      keywords = {Dental Plaque Detection, CNN, Image Processing.},
      month = {November},
  }