Human-visual-system-based fusion of multimodality 3D neuroimagery using brain-shift-compensating finite-element-based deformable models

Jacques G. Verly; Lara M. Vigneron; Nicolas Petitjean; Christophe Martin; Raluca Guran; Romain Boman; Pierre A. Robe

doi:10.1117/12.487088

Human-visual-system-based fusion of multimodality 3D neuroimagery using brain-shift-compensating finite-element-based deformable models

Jacques G. Verly^*, Lara M. Vigneron, Nicolas Petitjean, Christophe Martin, Raluca Guran, Romain Boman, Pierre A. Robe

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Our goal is to fuse multimodality imagery to enhance image-guided neurosurgery. Images that need to be fused must be registered. Registration becomes a challenge when the imaged object deforms between the times the images to be fused are taken. This is the case when "brain-shift" occurs. We begin by describing our strategy for nonrigid registration via finite-element methods. Then, we independently discuss an image fusion strategy based on a model of the human visual system. We illustrate the operation of many components of the registration system and the operation of the fusion system.

Original language	English
Pages (from-to)	338-349
Number of pages	12
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	5029
DOIs	https://doi.org/10.1117/12.487088
Publication status	Published - 2003
Externally published	Yes
Event	Medical Imaging 2003: Visualization, Image-Guided Procedures and Display - San Diego, CA, United States Duration: 16 Feb 2003 → 18 Feb 2003

Keywords

Brain-shift
Cortex segmentation
Finite elements
ICP
ITK
Level set
Medical imaging
Multi-modality fusion
Neuroimaging
Neuronavigation
Neurosurgery
Nonrigid registration
SPM
Surface mesh
Volume mesh
Warping

Access to Document

10.1117/12.487088

Cite this

@article{d81f8e8865ca4947a301eb8622eb27a6,

title = "Human-visual-system-based fusion of multimodality 3D neuroimagery using brain-shift-compensating finite-element-based deformable models",

abstract = "Our goal is to fuse multimodality imagery to enhance image-guided neurosurgery. Images that need to be fused must be registered. Registration becomes a challenge when the imaged object deforms between the times the images to be fused are taken. This is the case when {"}brain-shift{"} occurs. We begin by describing our strategy for nonrigid registration via finite-element methods. Then, we independently discuss an image fusion strategy based on a model of the human visual system. We illustrate the operation of many components of the registration system and the operation of the fusion system.",

keywords = "Brain-shift, Cortex segmentation, Finite elements, ICP, ITK, Level set, Medical imaging, Multi-modality fusion, Neuroimaging, Neuronavigation, Neurosurgery, Nonrigid registration, SPM, Surface mesh, Volume mesh, Warping",

author = "Verly, {Jacques G.} and Vigneron, {Lara M.} and Nicolas Petitjean and Christophe Martin and Raluca Guran and Romain Boman and Robe, {Pierre A.}",

year = "2003",

doi = "10.1117/12.487088",

language = "English",

volume = "5029",

pages = "338--349",

note = "Medical Imaging 2003: Visualization, Image-Guided Procedures and Display ; Conference date: 16-02-2003 Through 18-02-2003",

}

Human-visual-system-based fusion of multimodality 3D neuroimagery using brain-shift-compensating finite-element-based deformable models. / Verly, Jacques G.; Vigneron, Lara M.; Petitjean, Nicolas et al.
In: Proceedings of SPIE - The International Society for Optical Engineering, Vol. 5029, 2003, p. 338-349.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - Human-visual-system-based fusion of multimodality 3D neuroimagery using brain-shift-compensating finite-element-based deformable models

AU - Verly, Jacques G.

AU - Vigneron, Lara M.

AU - Petitjean, Nicolas

AU - Martin, Christophe

AU - Guran, Raluca

AU - Boman, Romain

AU - Robe, Pierre A.

PY - 2003

Y1 - 2003

N2 - Our goal is to fuse multimodality imagery to enhance image-guided neurosurgery. Images that need to be fused must be registered. Registration becomes a challenge when the imaged object deforms between the times the images to be fused are taken. This is the case when "brain-shift" occurs. We begin by describing our strategy for nonrigid registration via finite-element methods. Then, we independently discuss an image fusion strategy based on a model of the human visual system. We illustrate the operation of many components of the registration system and the operation of the fusion system.

AB - Our goal is to fuse multimodality imagery to enhance image-guided neurosurgery. Images that need to be fused must be registered. Registration becomes a challenge when the imaged object deforms between the times the images to be fused are taken. This is the case when "brain-shift" occurs. We begin by describing our strategy for nonrigid registration via finite-element methods. Then, we independently discuss an image fusion strategy based on a model of the human visual system. We illustrate the operation of many components of the registration system and the operation of the fusion system.

KW - Brain-shift

KW - Cortex segmentation

KW - Finite elements

KW - ICP

KW - ITK

KW - Level set

KW - Medical imaging

KW - Multi-modality fusion

KW - Neuroimaging

KW - Neuronavigation

KW - Neurosurgery

KW - Nonrigid registration

KW - SPM

KW - Surface mesh

KW - Volume mesh

KW - Warping

UR - http://www.scopus.com/inward/record.url?scp=0041624140&partnerID=8YFLogxK

U2 - 10.1117/12.487088

DO - 10.1117/12.487088

M3 - Article

AN - SCOPUS:0041624140

SN - 0277-786X

VL - 5029

SP - 338

EP - 349

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Medical Imaging 2003: Visualization, Image-Guided Procedures and Display

Y2 - 16 February 2003 through 18 February 2003

ER -

Human-visual-system-based fusion of multimodality 3D neuroimagery using brain-shift-compensating finite-element-based deformable models

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this