Journal Article10.1016/J.MEDIA.2010.03.005
A review of 3D/2D registration methods for image-guided interventions
837
TL;DR: The 3D/2D registration methods are reviewed with respect to image modality, image dimensionality, registration basis, geometric transformation, user interaction, optimization procedure, subject, and object of registration.
read more
About: This article is published in Medical Image Analysis. The article was published on 01 Apr 2012. The article focuses on the topics: Patient registration & Image registration.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Catheter navigation support for mechanical thrombectomy guidance: 3D/2D multimodal catheter-based registration with no contrast dye fluoroscopy.
Aurélien de Turenne,François Eugène,Raphaël Blanc,J. Szewczyk,Pascal Haigron +4 more
TL;DR: A new registration method compatible with no contrast dye fluoroscopy has been proposed to guide the crossing from aortic arch to a carotid in mechanical thrombectomy.
Increasing the Automation of a 2D-3D Registration System
TL;DR: Results show these methods can remove the need for manual vertebra identification during initial pose estimation, and were also very effective for result verification, producing a combined true positive rate of 100% and false positive rate equal to zero.
Non-Rigid 2D-3D Registration Using Convolutional Autoencoders
Peixin Li,Yuru Pei,Yuke Guo,Gengyu Ma,Tianmin Xu,Hongbin Zha +5 more
- 03 Apr 2020
TL;DR: A novel neural network-based framework for the non-rigid 2D-3D registration of the lateral cephalogram and the volumetric cone-beam CT (CBCT) images is proposed and a decoder is designed to generate digitally reconstructed radiographs (DRRs) from the non -rigidly deformed volumetrical image determined by the code vector.
[A 3D/2D registration method based on reconstruction of orthogonal-view Xray images].
J. Mi,Y. Zhou,Q. Feng +2 more
TL;DR: The proposed method can achieve robust and accurate 3D/2D registration at a speed that meets real-time requirements to improve the performance of spine surgery navigation.
A spatial registration method based on 2D-3D registration for an augmented reality spinal surgery navigation system.
Jingqi Zhang,Zhiyong Yang,Shan Jiang,Zeyang Zhou +3 more
- 19 Dec 2023
TL;DR: The spatial registration method based on 2D/3D registration technology can be used in AR spinal surgery navigation systems and is highly accurate and minimally invasive.
References
A method for registration of 3-D shapes
Paul J. Besl,H.D. McKay +1 more
TL;DR: In this paper, the authors describe a general-purpose representation-independent method for the accurate and computationally efficient registration of 3D shapes including free-form curves and surfaces, based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point.
20.6K
Multimodality image registration by maximization of mutual information
TL;DR: The results demonstrate that subvoxel accuracy with respect to the stereotactic reference solution can be achieved completely automatically and without any prior segmentation, feature extraction, or other preprocessing steps which makes this method very well suited for clinical applications.
Light field rendering
Marc Levoy,Pat Hanrahan +1 more
- 01 Aug 1996
TL;DR: This paper describes a sampled representation for light fields that allows for both efficient creation and display of inward and outward looking views, and describes a compression system that is able to compress the light fields generated by more than a factor of 100:1 with very little loss of fidelity.
Closed-form solution of absolute orientation using unit quaternions
TL;DR: A closed-form solution to the least-squares problem for three or more paints is presented, simplified by use of unit quaternions to represent rotation.
Least-Squares Fitting of Two 3-D Point Sets
TL;DR: An algorithm for finding the least-squares solution of R and T, which is based on the singular value decomposition (SVD) of a 3 × 3 matrix, is presented.