Automatic design and 3D segmentation of mandible bone using CNN algorithm via exclusive GUI

Subject Areas : Biomedical Spectroscopy, Microscopy, Imaging, Endoscopy

Nadia MehradKia ¹ , Shakiba Mohammadi ² , Sayedali Mousavi ³

1 - Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran.
2 - Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran.
3 - Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran.

Received: 2023-11-15 Accepted : 2024-01-16 Published : 2024-02-05

Keywords: Segmentation, FCN, Mandible, Alveolar neural canal, CBCT, U-net,

Abstract :

Nowadays scientists are looking for decreasing dental faults by presenting new approaches.It is obvious that comprehensive information about the anatomic position of the inferior alveolar neuralcanal is essential to have the most ideal mandible surgery or systemic tooth implant. Accordingly, wepresent a new approach in this article that can be used to have 3D segmentation and recognition of thementioned canal in mandible by CBCT image. This approach includes two main steps. In the first step,we train a full convolutional 3D net (FCN) to reach the ability of section recognition, which can recognizethe relevant area of mandible bone. And in the next step, we define a 3D U-net, which is similar to FCN,to segment the inferior Alveolar neural (IAN) canal from the lower jaw. Evaluated on publicly availabledatasets, our method achieved an average Dice coefficient of 86.61%.

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