锥形束计算机断层扫描(CBCT)广泛应用于现代牙科,牙齿分割构成了基于这些成像数据的数字工作流程的组成部分。先前的方法严重依赖于手动分割,并且在临床实践中是耗时且费力的。最近,随着计算机视觉技术的进步,学者们进行了深入的研究,提出了各种快速准确的牙齿分割方法。在这次审查中,我们回顾了该领域的55篇文章,并讨论了其有效性,优势,以及每种方法的缺点。除了简单的分类和讨论,本文旨在揭示如何通过应用和改进现有的图像分割算法来改进牙齿分割方法,以解决诸如牙齿形态不规则和边界模糊等问题。假设随着这些方法的优化,手工操作将减少,和更高的精度和鲁棒性的牙齿分割将实现。最后,我们强调了这一领域仍然存在的挑战,并为未来的方向提供了前景。
Cone beam computed tomography (CBCT) is widely employed in modern dentistry, and tooth segmentation constitutes an integral part of the digital workflow based on these imaging data. Previous methodologies rely heavily on manual segmentation and are time-consuming and labor-intensive in clinical practice. Recently, with advancements in computer vision technology, scholars have conducted in-depth research, proposing various fast and accurate tooth segmentation methods. In this
review, we
review 55 articles in this field and discuss the effectiveness, advantages, and disadvantages of each approach. In addition to simple classification and discussion, this
review aims to reveal how tooth segmentation methods can be improved by the application and refinement of existing image segmentation algorithms to solve problems such as irregular morphology and fuzzy boundaries of teeth. It is assumed that with the optimization of these methods, manual operation will be reduced, and greater accuracy and robustness in tooth segmentation will be achieved. Finally, we highlight the challenges that still exist in this field and provide prospects for future directions.