Nonrigid iterative closest points for registration of 3D biomedical surfaces

Luming LIANG, Mingqiang WEI*, Andrzej SZYMCZAK, Anthony PETRELLA, Haoran XIE, Jing QIN, Jun WANG, Fu Lee WANG

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)

16 Citations (Scopus)

Abstract

Advanced 3D optical and laser scanners bring new challenges to computer graphics. We present a novel nonrigid surface registration algorithm based on Iterative Closest Point (ICP) method with multiple correspondences. Our method, called the Nonrigid Iterative Closest Points (NICPs), can be applied to surfaces of arbitrary topology. It does not impose any restrictions on the deformation, e.g. rigidity or articulation. Finally, it does not require parametrization of input meshes. Our method is based on an objective function that combines distance and regularization terms. Unlike the standard ICP, the distance term is determined based on multiple two-way correspondences rather than single one-way correspondences between surfaces. A Laplacian-based regularization term is proposed to take full advantage of multiple two-way correspondences. This term regularizes the surface movement by enforcing vertices to move coherently with their 1-ring neighbors. The proposed method achieves good performances when no global pose differences or significant amount of bending exists in the models, for example, families of similar shapes, like human femur and vertebrae models.

Original languageEnglish
Pages (from-to)141-154
Number of pages14
JournalOptics and Lasers in Engineering
Volume100
Early online date10 Aug 2017
DOIs
Publication statusPublished - Jan 2018
Externally publishedYes

Fingerprint

optical scanners
vertebrae
femur
computer graphics
Computer graphics
rigidity
Rigidity
scanners
mesh
constrictions
apexes
topology
Topology
Lasers
rings
lasers

Keywords

  • Bone
  • Multiple two-way correspondences
  • Nonrigid iterative closest points (NICPs)
  • Surface registration

Cite this

LIANG, Luming ; WEI, Mingqiang ; SZYMCZAK, Andrzej ; PETRELLA, Anthony ; XIE, Haoran ; QIN, Jing ; WANG, Jun ; WANG, Fu Lee. / Nonrigid iterative closest points for registration of 3D biomedical surfaces. In: Optics and Lasers in Engineering. 2018 ; Vol. 100. pp. 141-154.
@article{23bae8223d114265a8f2eb0ebc9f4b0c,
title = "Nonrigid iterative closest points for registration of 3D biomedical surfaces",
abstract = "Advanced 3D optical and laser scanners bring new challenges to computer graphics. We present a novel nonrigid surface registration algorithm based on Iterative Closest Point (ICP) method with multiple correspondences. Our method, called the Nonrigid Iterative Closest Points (NICPs), can be applied to surfaces of arbitrary topology. It does not impose any restrictions on the deformation, e.g. rigidity or articulation. Finally, it does not require parametrization of input meshes. Our method is based on an objective function that combines distance and regularization terms. Unlike the standard ICP, the distance term is determined based on multiple two-way correspondences rather than single one-way correspondences between surfaces. A Laplacian-based regularization term is proposed to take full advantage of multiple two-way correspondences. This term regularizes the surface movement by enforcing vertices to move coherently with their 1-ring neighbors. The proposed method achieves good performances when no global pose differences or significant amount of bending exists in the models, for example, families of similar shapes, like human femur and vertebrae models.",
keywords = "Bone, Multiple two-way correspondences, Nonrigid iterative closest points (NICPs), Surface registration",
author = "Luming LIANG and Mingqiang WEI and Andrzej SZYMCZAK and Anthony PETRELLA and Haoran XIE and Jing QIN and Jun WANG and WANG, {Fu Lee}",
year = "2018",
month = "1",
doi = "10.1016/j.optlaseng.2017.08.005",
language = "English",
volume = "100",
pages = "141--154",
journal = "Optics and Lasers in Engineering",
issn = "0143-8166",
publisher = "Elsevier Ltd",

}

Nonrigid iterative closest points for registration of 3D biomedical surfaces. / LIANG, Luming; WEI, Mingqiang; SZYMCZAK, Andrzej; PETRELLA, Anthony; XIE, Haoran; QIN, Jing; WANG, Jun; WANG, Fu Lee.

In: Optics and Lasers in Engineering, Vol. 100, 01.2018, p. 141-154.

Research output: Journal PublicationsJournal Article (refereed)

TY - JOUR

T1 - Nonrigid iterative closest points for registration of 3D biomedical surfaces

AU - LIANG, Luming

AU - WEI, Mingqiang

AU - SZYMCZAK, Andrzej

AU - PETRELLA, Anthony

AU - XIE, Haoran

AU - QIN, Jing

AU - WANG, Jun

AU - WANG, Fu Lee

PY - 2018/1

Y1 - 2018/1

N2 - Advanced 3D optical and laser scanners bring new challenges to computer graphics. We present a novel nonrigid surface registration algorithm based on Iterative Closest Point (ICP) method with multiple correspondences. Our method, called the Nonrigid Iterative Closest Points (NICPs), can be applied to surfaces of arbitrary topology. It does not impose any restrictions on the deformation, e.g. rigidity or articulation. Finally, it does not require parametrization of input meshes. Our method is based on an objective function that combines distance and regularization terms. Unlike the standard ICP, the distance term is determined based on multiple two-way correspondences rather than single one-way correspondences between surfaces. A Laplacian-based regularization term is proposed to take full advantage of multiple two-way correspondences. This term regularizes the surface movement by enforcing vertices to move coherently with their 1-ring neighbors. The proposed method achieves good performances when no global pose differences or significant amount of bending exists in the models, for example, families of similar shapes, like human femur and vertebrae models.

AB - Advanced 3D optical and laser scanners bring new challenges to computer graphics. We present a novel nonrigid surface registration algorithm based on Iterative Closest Point (ICP) method with multiple correspondences. Our method, called the Nonrigid Iterative Closest Points (NICPs), can be applied to surfaces of arbitrary topology. It does not impose any restrictions on the deformation, e.g. rigidity or articulation. Finally, it does not require parametrization of input meshes. Our method is based on an objective function that combines distance and regularization terms. Unlike the standard ICP, the distance term is determined based on multiple two-way correspondences rather than single one-way correspondences between surfaces. A Laplacian-based regularization term is proposed to take full advantage of multiple two-way correspondences. This term regularizes the surface movement by enforcing vertices to move coherently with their 1-ring neighbors. The proposed method achieves good performances when no global pose differences or significant amount of bending exists in the models, for example, families of similar shapes, like human femur and vertebrae models.

KW - Bone

KW - Multiple two-way correspondences

KW - Nonrigid iterative closest points (NICPs)

KW - Surface registration

UR - http://www.scopus.com/inward/record.url?scp=85030830756&partnerID=8YFLogxK

U2 - 10.1016/j.optlaseng.2017.08.005

DO - 10.1016/j.optlaseng.2017.08.005

M3 - Journal Article (refereed)

AN - SCOPUS:85030830756

VL - 100

SP - 141

EP - 154

JO - Optics and Lasers in Engineering

JF - Optics and Lasers in Engineering

SN - 0143-8166

ER -