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Low‐dose three‐dimensional reconstruction of the femur with unit free‐form deformation
Author(s) -
Zeng Xiangsen,
Wang Chentao,
Zhou Hai,
Wei Shan,
Chen Xiaojun
Publication year - 2014
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4887816
Subject(s) - silhouette , femur , iterative reconstruction , reproducibility , artificial intelligence , computer vision , mean squared error , mathematics , free form deformation , computer science , deformation (meteorology) , nuclear medicine , materials science , medicine , statistics , surgery , composite material
Purpose: This paper describes a low‐dose method for reconstructing three‐dimensional models of femur, using a standard shape model (SSM) and two conventional x‐ray images. Methods: The x‐ray images were taken in two orthogonal directions. The x‐ray source and sensor configurations were documented. An optimized algorithm was employed to align the x‐ray image to the three‐dimensional model. A method of direct correspondence building is proposed for linking two‐dimensional images with three‐dimensional projections of a SSM. The reconstruction method proposed in this paper is based on a SSM, which was adapted for x‐ray images of individual bones. The adaption was executed by deforming the template bone shape until its silhouette boundary exactly matched the x‐ray image of the individual bone. A silhouette‐based unit free‐form deformation method was evaluated for its suitability in the adaption of the SSM for x‐ray images. Comprehensive experiments were designed and conducted for 35 specimens. Results: The validity of the low‐dose reconstruction method was demonstrated for the femur, with good results for accuracy (mean error of 1.1 mm, root‐mean‐square error of 2.1 mm), reproducibility (intraobservation coefficient of variation of 1.1%, interobservation coefficient of variation of 1.4%), and time consumption (mean of 5 min for a full femur). Conclusions: Once this approach has been validated in vivo , it should be suited to multiple applications of routine clinical and research practices.