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Related Concept Videos

Tooth Anatomy01:21

Tooth Anatomy

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The human tooth enables us to eat a variety of foods, speak clearly, and even aid in shaping our faces. Teeth are composed of various elements that work together. Here's a detailed look at the anatomy of a human tooth.
The Crown, Neck, and Root
The visible part of the tooth is referred to as the crown. It's covered by enamel, the hardest substance in the human body. The crown is uniquely shaped for each type of tooth, allowing for different functions such as cutting, tearing, or...
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Precision Oral Medicine: A DPR Segmentation and Transfer Learning Approach for Detecting Third Molar Compress

Yuan-Jin Lin1, Shih-Lun Chen2, Yi-Cheng Mao3

  • 1Department of Program on Semiconductor Manufacturing TechnologyAcademy of Innovative Semiconductor and Sustainable ManufacturingNational Cheng Kung University Tainan 701401 Taiwan.

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This study introduces an AI-powered method using dental panoramic radiography to detect if mandibular third molars compress the inferior alveolar nerve, improving accuracy and reducing radiation exposure.

Keywords:
Inferior alveolar nerveimage maskingimage segmentationobject detectionthird molarvision transformer

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Area of Science:

  • Oral Surgery
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Mandibular third molar extraction is common, with neurological risks requiring careful preoperative assessment.
  • Identifying inferior alveolar nerve compression by third molars is crucial but currently relies on time-consuming manual analysis.
  • Reducing reliance on CT scans for diagnosis is desirable due to radiation exposure concerns.

Purpose of the Study:

  • To develop an automated system using dental panoramic radiography to classify third molar compression of the inferior alveolar nerve.
  • To improve diagnostic accuracy and efficiency in preoperative assessments for mandibular third molar surgery.
  • To reduce the need for computed tomography (CT) scans in diagnosing nerve compression.

Main Methods:

  • Implemented a novel dental panoramic radiography segmentation technique for third molar localization.
  • Employed an innovative edge masking enhancement method to extract features of the inferior alveolar nerve and third molar.
  • Utilized a transformer-based image detection model for classification of nerve compression.

Main Results:

  • The third molar position localization achieved 97.92% accuracy, an improvement of 3.6% over prior research.
  • Edge masking and image enhancement methods increased classification accuracy by 4.3%.
  • Maximum accuracy reached 98.45% when supplemented with CT scans, a 4.5% improvement over previous studies.

Conclusions:

  • The proposed AI-driven approach effectively identifies third molar compression of the inferior alveolar nerve using dental panoramic radiography.
  • The innovative segmentation and feature extraction techniques significantly enhance diagnostic accuracy.
  • This method offers a promising alternative to reduce CT scan utilization and associated radiation risks in preoperative evaluations.