Anatomically Plausible Surface Alignment and Reconstruction

Rasmus Reinhold Paulsen, Rasmus Larsen

AbstractWith the increasing clinical use of 3D surface scanners there
is a need for accurate and reliable algorithms that can produce anatomi-
cally plausible surfaces. In this paper, a combined method for surface
alignment and reconstruction is proposed. It is based on an implicit
surface representation combined with a Markov Random Field regular-
isation method. Conceptually, the method maintains an implicit ideal
description of the sought surface. This implicit surface is iteratively up-
dated by realigning the input point sets and Markov Random Field reg-
ularisation. The regularisation is based on a prior energy that has earlier
proved to be particularly well suited to human surface scans. The method
has been tested on full cranial scans of ten test subjects and on several
scans of the outer human ear.
Keywordssurface reconstruction, markov random fields
TypeConference paper [With referee]
ConferenceProceedings of Theory and Practice of Computer Graphics - TPCG 2010 (Eurographics UK)
EditorsJohn Collomosse (University of Surrey) and Ian Grimstead (Cardiff University)
Year2010    Month September
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Image Analysis & Computer Graphics