Sparse Constrained Transformation Model Based on Radial Basis Function Expansion: Application to Cardiac and Brain Image Registration

Sparse Constrained Transformation Model Based on Radial Basis Function Expansion: Application to Cardiac and Brain Image Registration

Estimating robust transformations based on noisy landmark correspondences is challenging and cannot be ensured to be exact. In this paper, we propose a novel sparse transformation model based on corresponding landmarks. First, we construct a new transformation model that uses compact supported radia...

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Bibliographic Details
Main Authors: Zhengrui Zhang, Xuan Yang, Yan-Ran Li, Guoliang Chen
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Spatial transformation
image registration
regularization
sparse model
Online Access:https://ieeexplore.ieee.org/document/8421570/

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