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Optimizing dental implant identification using deep learning leveraging artificial data.

Shintaro Sukegawa1,2, Kazumasa Yoshii3, Takeshi Hara4,5

  • 1Department of Oral and Maxillofacial Surgery, Faculty of Medicine, Kagawa University, 1750-1, Ikenobe, Miki-cho, Kita-gun, Takamatsu, 761-0793, Kagawa, Japan. gouwan19@gmail.com.

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Generating artificial dental implant images improved classification accuracy in panoramic X-rays. This deep learning approach enhances diagnostic performance by supplementing real-world data with realistic synthetic images.

Keywords:
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Area of Science:

  • Biomedical Imaging
  • Artificial Intelligence in Dentistry
  • Deep Learning for Medical Diagnosis

Background:

  • Accurate dental implant classification is crucial for diagnosis and treatment planning.
  • Existing datasets for deep learning models may lack diversity and volume.
  • Artificial image generation offers a potential solution to augment limited datasets.

Purpose of the Study:

  • To assess the impact of incorporating artificially generated dental implant images on classification performance.
  • To compare the effectiveness of different artificial image generation strategies.
  • To enhance the accuracy of deep learning models for dental implant identification using panoramic X-rays.

Main Methods:

  • A dataset of 7,946 in vivo dental implant images was supplemented with artificially generated images.
  • Three-dimensional scanning was used to create implant surface models for image generation.
  • ResNet50 deep learning model was employed to classify 10 types of dental implants across three datasets: in vivo, artificial without background adjustment, and artificial with background adjustment.

Main Results:

  • Classification accuracy for in vivo images (Dataset A) was 0.8888.
  • Accuracy for artificial images without background adjustment (Dataset B) was 0.903.
  • Accuracy for artificial images with background adjustment (Dataset C) was highest at 0.9146, showing optimal feature distribution.

Conclusions:

  • Incorporating artificially generated X-ray images of dental implants significantly enhances deep learning classification model performance.
  • Artificial image generation, particularly with background adjustments, is a beneficial strategy for improving dental implant classification accuracy.
  • This method shows promise for advancing AI-driven diagnostics in dentistry using panoramic radiography.