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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Detaylı Bibliyografya
Asıl Yazarlar:	Zhengrui Zhang, Xuan Yang, Yan-Ran Li, Guoliang Chen
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	IEEE 2018-01-01
Seri Bilgileri:	IEEE Access
Konular:	Spatial transformation image registration regularization sparse model
Online Erişim:	https://ieeexplore.ieee.org/document/8421570/
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Sparse Constrained Transformation Model Based on Radial Basis Function Expansion: Application to Cardiac and Brain Image Registration

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