Non-rigid Image Registration Using a Statistical Spline Deformation Model

Dirk Loeckx; Frederik Maes; Dirk Vandermeulen; Paul Suetens

doi:10.1007/978-3-540-45087-0_39

ScienceGate Book Chapters

JOURNAL ARTICLE

Non-rigid Image Registration Using a Statistical Spline Deformation Model

Dirk Loeckx Frederik Maes Dirk Vandermeulen Paul Suetens

Year: 2003 Journal: Lecture notes in computer science Vol: 18 Pages: 463-474 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-540-45087-0_39

Get Full-Text PDF Get Analytical Report

Keywords:

Affine transformation Spline (mechanical) Principal component analysis Computer science Image registration Artificial intelligence Degrees of freedom (physics and chemistry) Computer vision Transformation (genetics) B-spline Deformation (meteorology) Image (mathematics) Algorithm Pattern recognition (psychology) Mathematics Geometry Mathematical analysis Engineering Structural engineering

Metrics

Cited By

1.12

FWCI (Field Weighted Citation Impact)

Refs

0.75

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Medical Image Segmentation Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Medical Imaging and Analysis

Physical Sciences → Engineering → Biomedical Engineering

Image and Object Detection Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Non-rigid Image Registration Using a Statistical Spline Deformation Model

Metrics

Citation History

Topics

Related Documents

Non-rigid brain image registration using a statistical deformation model

Non-rigid Groupwise Registration using B-Spline Deformation Model

Non-rigid free-form 2D–3D registration using a B-spline-based statistical deformation model

Non-rigid free-form 2D–3D registration using a B-spline-based statistical deformation model

Non-rigid Free-Form 2D-3D Registration Using Statistical Deformation Model