Jul 27, 2018 · First, we construct a new transformation model that uses compact supported radial basis functions (CSRBFs) with multiple supports, with a least- ...

To evaluate its image registration perfor- mance, the second and third parts are, respectively, clinical brain and children cardiac image registration ...

Sparse Constrained Transformation Model Based on Radial Basis Function Expansion: Application to Cardiac and Brain Image Registration · Medicine, Computer ...

In this paper, we propose a novel sparse transformation model based on corresponding landmarks. First, we construct a new transformation model that uses compact ...

2018: Sparse Constrained Transformation Model Based on Radial Basis Function Expansion: Application to Cardiac and Brain Image Registration IEEE Access 6 ...

Sparse Constrained Transformation Model Based on Radial Basis Function Expansion: Application to Cardiac and Brain Image Registration. 2018, IEEE Access. 4D ...

Landmark-based registration using radial basis functions (RBF) is an efficient and mathematically transparent method for the registration of medical images.

Sparse Constrained Transformation Model Based on Radial Basis Function Expansion: Application to Cardiac and Brain Image Registration · Zhengrui ZhangXuan S ...

2018: Sparse Constrained Transformation Model Based on Radial Basis Function Expansion: Application to Cardiac and Brain Image Registration IEEE Access 6 ...

Linear elastic models have also been used when registering brain images based on sparse correspondences. Davatzikos [18] first used geometric characteristics to ...