Cargando…
Fast Groupwise Registration Using Multi-Level and Multi-Resolution Graph Shrinkage
Groupwise registration aligns a set of images to a common space. It can however be inefficient and ineffective when dealing with datasets with significant anatomical variations. To mitigate these problems, we propose a groupwise registration framework based on hierarchical multi-level and multi-reso...
Autores principales: | Dong, Pei, Cao, Xiaohuan, Yap, Pew-Thian, Shen, Dinggang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6722141/ https://www.ncbi.nlm.nih.gov/pubmed/31481695 http://dx.doi.org/10.1038/s41598-019-48491-9 |
Ejemplares similares
-
eHUGS: Enhanced Hierarchical Unbiased Graph Shrinkage for Efficient Groupwise Registration
por: Wu, Guorong, et al.
Publicado: (2016) -
Deep Learning Deformation Initialization for Rapid Groupwise Registration of Inhomogeneous Image Populations
por: Ahmad, Sahar, et al.
Publicado: (2019) -
Multi-channel framelet denoising of diffusion-weighted images
por: Chen, Geng, et al.
Publicado: (2019) -
A Review of Point Set Registration: From Pairwise Registration to Groupwise Registration
por: Zhu, Hao, et al.
Publicado: (2019) -
4D Multi-Modality Tissue Segmentation of Serial Infant Images
por: Wang, Li, et al.
Publicado: (2012)