Literature DB >> 21257360

Automatic extraction of inferior alveolar nerve canal using feature-enhancing panoramic volume rendering.

Gyehyun Kim1, Jeongjin Lee, Ho Lee, Jinwook Seo, Yun-Mo Koo, Yeong-Gil Shin, Bohyoung Kim.   

Abstract

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.

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Year:  2011        PMID: 21257360     DOI: 10.1109/TBME.2010.2089053

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  7 in total

1.  Accuracy of software designed for automated localization of the inferior alveolar nerve canal on cone beam CT images.

Authors:  Ehsan Bahrampour; Ali Zamani; Sadegh Kashkouli; Elham Soltanimehr; Mohsen Ghofrani Jahromi; Zahra Sanaeian Pourshirazi
Journal:  Dentomaxillofac Radiol       Date:  2015-12-14       Impact factor: 2.419

2.  Evaluation of the diagnostic efficacy of two cone beam computed tomography protocols in reliably detecting the location of the inferior alveolar nerve canal.

Authors:  Aditya Tadinada; Sydney Schneider; Sumit Yadav
Journal:  Dentomaxillofac Radiol       Date:  2017-03-13       Impact factor: 2.419

3.  Tracking of the inferior alveolar nerve: its implication in surgical planning.

Authors:  Jimoh O Agbaje; Elke Van de Casteele; Ahmed S Salem; Dickson Anumendem; Ivo Lambrichts; Constantinus Politis
Journal:  Clin Oral Investig       Date:  2016-11-22       Impact factor: 3.573

4.  Automatic segmentation of mandibular canal in cone beam CT images using conditional statistical shape model and fast marching.

Authors:  Fatemeh Abdolali; Reza Aghaeizadeh Zoroofi; Maryam Abdolali; Futoshi Yokota; Yoshito Otake; Yoshinobu Sato
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-09-21       Impact factor: 2.924

5.  Validation of different protocols of inferior alveolar canal tracing using cone beam computed tomography (CBCT).

Authors:  Ali Fahd; Ahmed Talaat Temerek; Sarah Mohammed Kenawy
Journal:  Dentomaxillofac Radiol       Date:  2022-03-04       Impact factor: 3.525

Review 6.  Visualization techniques of the inferior alveolar nerve (IAN): a narrative review.

Authors:  Annelies Weckx; Jimoh Olubanwo Agbaje; Yi Sun; Reinhilde Jacobs; Constantinus Politis
Journal:  Surg Radiol Anat       Date:  2015-07-12       Impact factor: 1.246

7.  Fast and Accurate Semiautomatic Segmentation of Individual Teeth from Dental CT Images.

Authors:  Ho Chul Kang; Chankyu Choi; Juneseuk Shin; Jeongjin Lee; Yeong-Gil Shin
Journal:  Comput Math Methods Med       Date:  2015-08-27       Impact factor: 2.238

  7 in total

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