Abstract

Medical imaging techniques, such as (cone beam) computed tomography and magnetic resonance imaging, have proven to be a valuable component for oral and maxillofacial surgery (OMFS). Accurate segmentation of the mandible from head and neck (H&N) scans is an important step in order to build a personalized 3D digital mandible model for 3D printing and treatment planning of OMFS. Segmented mandible structures are used to effectively visualize the mandible volumes and to evaluate particular mandible properties quantitatively. However, mandible segmentation is always challenging for both clinicians and researchers, due to complex structures and higher attenuation materials, such as teeth (filling) or metal implants that easily lead to high noise and strong artifacts during scanning. Moreover, the size and shape of the mandible vary to a large extent between individuals. Therefore, mandible segmentation is a tedious and time-consuming task and requires adequate training to be performed properly. With the advancement of computer vision approaches, researchers have developed several algorithms to automatically segment the mandible during the last two decades. The objective of this review was to present the available fully (semi)automatic segmentation methods of the mandible published in different scientific articles. This review provides a vivid description of the scientific advancements to clinicians and researchers in this field to help develop novel automatic methods for clinical applications.

Highlights

  • Three-dimensional (3D) medical imaging techniques have a fundamental role in the field of oral and maxillofacial surgery (OMFS) [1,2]. 3D images are used to guide diagnosis, assess the severity of disease and for pre-operative planning and per-operative guidance using 3D images and virtual surgical planning (VSP) [3]

  • Studies have shown that 3D VSP requires accurate segmentation of the mandible, which is currently performed by medical technicians [4,6]

  • We collected 77 publications focused on mandible segmentation or organs at risk (OARs) segmentation in the head and neck (H&N) region

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Summary

Introduction

Three-dimensional (3D) medical imaging techniques have a fundamental role in the field of oral and maxillofacial surgery (OMFS) [1,2]. 3D images are used to guide diagnosis, assess the severity of disease and for pre-operative planning and per-operative guidance using 3D images and virtual surgical planning (VSP) [3]. 3D images are used to guide diagnosis, assess the severity of disease and for pre-operative planning and per-operative guidance using 3D images and virtual surgical planning (VSP) [3]. In the field of oral cancer, where surgical resection requiring the partial removal of the mandible is a common treatment, resection surgery is often based on 3D VSP to accurately design a resection plan around tumor margins [4]. Studies have shown that 3D VSP requires accurate segmentation of the mandible, which is currently performed by medical technicians [4,6]. Especially for 3D VSP, was usually done manually, which is a time-consuming and poorly reproducible process [7,8]

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