Automatic extraction of inferior alveolar nerve canal using feature-enhancing panoramic volume rendering.
Dental implant surgery, which involves the surgical insertion of a dental implant into the jawbone as an artificial root, has become one of the most successful applications of computed tomography (CT) in dental implantology. For successful implant surgery, it is essential to identify vital anatomic structures such as the inferior alveolar nerve (IAN), which should be avoided during the surgical procedure. Due to the ambiguity of its structure, the IAN is very elusive to extract in dental CT images. As a result, the IAN canal is typically identified in most previous studies. This paper presents a novel method of automatically extracting the IAN canal. Mental and mandibular foramens, which are regarded as the ends of the IAN canal in the mandible, are detected automatically using 3-D panoramic volume rendering (VR) and texture analysis techniques. In the 3-D panoramic VR, novel color shading and compositing methods are proposed to emphasize the foramens and isolate them from other fine structures. Subsequently, the path of the IAN canal is computed using a line-tracking algorithm. Finally, the IAN canal is extracted by expanding the region of the path using a fast marching method with a new speed function exploiting the anatomical information about the canal radius. In experimental results using ten clinical datasets, the proposed method identified the IAN canal accurately, demonstrating that this approach assists dentists substantially during dental implant surgery.
School of Computer Scienceand Engineering, Seoul National University, Seoul 151-742, Korea. kgh31023@snu.ac.kr
Gyehyun
G
Kim
Jeongjin
J
Lee
Ho
H
Lee
Jinwook
J
Seo
Yun-Mo
YM
Koo
Yeong-Gil
YG
Shin
Bohyoung
B
Kim
D000465:Algorithms; D003757:Dental Implantation; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008340:Mandibular Nerve / Q000000981:diagnostic imaging*; D011861:Radiography, Dental / Q000379:methods*; D025321:Surgery, Computer-Assisted / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000379:methods*