Estimating anatomically-correct reference model for craniomaxillofacial deformity via sparse representation

Yi Ren, Li Wang, Yaozong Gao, Zhen Tang, Ken Chung Chen, Jianfu Li, Steve G.F. Shen, Jin Yan, Philip K.M. Lee, Ben Chow, James J. Xia, Dinggang Shen

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    5 Citations (Scopus)

    Abstract

    The success of craniomaxillofacial (CMF) surgery depends not only on the surgical techniques, but also upon an accurate surgical planning. However, surgical planning for CMF surgery is challenging due to the absence of a patient-specific reference model. In this paper, we present a method to automatically estimate an anatomically correct reference shape of jaws for the patient requiring orthognathic surgery, a common type of CMF surgery. We employ the sparse representation technique to represent the normal regions of the patient with respect to the normal subjects. The estimated representation is then used to reconstruct a patient-specific reference model with "restored" normal anatomy of the jaws. We validate our method on both synthetic subjects and patients. Experimental results show that our method can effectively reconstruct the normal shape of jaw for patients. Also, a new quantitative measurement is introduced to quantify the CMF deformity and validate the method in a quantitative approach, which is rarely used before.

    Original languageEnglish
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
    PublisherSpringer Verlag
    Pages73-80
    Number of pages8
    EditionPART 2
    ISBN (Print)9783319104690
    DOIs
    Publication statusPublished - 2014
    Event17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - Boston, MA, United States
    Duration: 2014 Sept 142014 Sept 18

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume8674 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
    Country/TerritoryUnited States
    CityBoston, MA
    Period14/9/1414/9/18

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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