title: Sparse shape model for fibular transfer planning in mandibular reconstruction.
abstract: In this paper, we propose an automated preoperative planning method that estimates a plan fitted to the data of a new patient using a planned dataset of previous patients. Although mandibular reconstruction with fibular segments needs preoperative planning for the precise placement of segments, recent interactive planning software cannot secure objectivity of the planning and time-consuming trial-and-error processes are required. The proposed method employs sparse shape modeling; in this modeling, we select a subset of the data from a prepared preoperative planning dataset to make an example or instance of reconstruction via a linear combination of the data. We conduct experiments using the dataset planned by medical doctors and compare the instance estimated by the proposed method to the manual placement by these doctors.
authors.forename: Riho
authors.initials: R
authors.lastname: Kawasaki
authors.forename: Megumi
authors.initials: M
authors.lastname: Nakao
authors.forename: Yuichiro
authors.initials: Y
authors.lastname: Imai
authors.forename: Nobuhiro
authors.initials: N
authors.lastname: Ueda
authors.forename: Toshihide
authors.initials: T
authors.lastname: Hatanaka
authors.forename: Mao
authors.initials: M
authors.lastname: Shiba
authors.forename: Tadaaki
authors.initials: T
authors.lastname: Kirita
authors.forename: Tetsuya
authors.initials: T
authors.lastname: Matsuda
mesh_terms: D066264:Datasets as Topic; D005360:Fibula / Q000601:surgery*; D006801:Humans; D008334:Mandible / Q000601:surgery; D063175:Mandibular Reconstruction; D008962:Models, Theoretical; D010347:Patient Care Planning; D012984:Software