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Non‐Rigid Surface Matching and Its Application to Scoliosis Modelling
Author(s) -
Ang KimSiang,
Mitchell Harvey L.
Publication year - 2010
Publication title -
the photogrammetric record
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 51
eISSN - 1477-9730
pISSN - 0031-868X
DOI - 10.1111/j.1477-9730.2010.00581.x
Subject(s) - surface (topology) , matching (statistics) , computer science , scoliosis , algorithm , rigid body , artificial intelligence , computer vision , mathematics , geometry , physics , medicine , statistics , surgery , classical mechanics
The registration of digital surface topographies has applications in cases requiring comparisons with previously derived data for the purpose of identifying surface change. A spatial data manipulation tool in the form of a non‐rigid surface matching algorithm with new parameters has been investigated, and is aimed at replacing the classical least squares 3D surface matching approach which allows positional fit rather than shape fit. A computer program has been written to implement the matching algorithm. A potential application in the medical field may result from the extensive use of surface topographies of back shapes to monitor scoliosis. So far, the analysis of back shape change to identify scoliotic progress has not been satisfactorily solved. As a contribution to this task, the capacity of the non‐rigid matching algorithm to find the match and simultaneously model the scoliotic deformities has been assessed. Analysis indicates that this new non‐rigid algorithm is an improvement on the classical rigid surface matching approach. The new parameters model and delineate the possible shape changes caused by scoliosis. The results show that this new non‐rigid algorithm not only assures the best positional fit but also the best shape fit.