Temporomandibular Joint Segmentation Using Deep Learning for Automated Three-Dimensional Reconstruction

Choi, Youngtae; Song, Ho‐Jun; Lee, Jae-Seo; Im, Yeong-Gwan

doi:10.14476/jomp.2024.49.4.109

Public

Temporomandibular Joint Segmentation Using Deep Learning for Automated Three-Dimensional Reconstruction

Published in Journal of Oral Medicine and Pain • Dec 24, 2024

Authors:

Youngtae Choi

Ho‐Jun Song

Jae-Seo Lee

Abstract

Purpose: Purpose: Cone beam computed tomography (CBCT) is widely used to evaluate the temporomandibular joint (TMJ).For the three-dimensional (3D) assessment of the TMJ, segmentation of the mandibular condyle and articular fossa is essential.This study aimed to perform deep learning-based 3D segment...

Subject

Temporomandibular joint

Segmentation

Artificial intelligence

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