Inter-group image registration by hierarchical graph shrinkage
Shihui Ying,Guorong Wu,Shu Liao,Dinggang Shen +3 more
- Vol. 2013, pp 1030-1033
Reads0
Chats0
TLDR
A novel inter-group image registration method to register different groups of images simultaneously, using a hierarchical two-level graph to model the distribution of entire images on the manifold, with intra-graph representing the image distribution in each group and the inter-graph describing the relationship between two groups.Abstract:
In this paper, we propose a novel inter-group image registration method to register different groups of images (e.g., young and elderly brains) simultaneously. Specifically, we use a hierarchical two-level graph to model the distribution of entire images on the manifold, with intra-graph representing the image distribution in each group and the inter-graph describing the relationship between two groups. Then the procedure of inter-group registration is formulated as a dynamic evolution of graph shrinkage. The advantage of our method is that the topology of entire image distribution is explored to guide the image registration. In this way, each image coordinates with its neighboring images on the manifold to deform towards the population center, by following the deformation pathway simultaneously optimized within the graph. Our proposed method has been also compared with other state-of-the-art inter-group registration methods, where our method achieves better registration results in terms of registration accuracy and robustness.read more
Citations
More filters
Journal ArticleDOI
A review on registration of medical images using graph theoretic approaches
R. Akshaya,Hema P Menon +1 more
TL;DR: This paper mainly discusses the methods that use the graph approach to register the medical images and gives a brief description of the methods present.
Groupwise whole-body MR image registration guided by zero-average volume changes
TL;DR: Imiomics (imaging-omics) is an image analysis technique developed at Uppsala University that allows statistical analysis of whole-body image data from scans of multiple subjects.
References
More filters
Book
Differential Geometry, Lie Groups, and Symmetric Spaces
TL;DR: In this article, the structure of semisimplepleasure Lie groups and Lie algebras is studied. But the classification of simple Lie algesbras and of symmetric spaces is left open.
Journal ArticleDOI
Unbiased Average Age-Appropriate Atlases for Pediatric Studies
Vladimir S. Fonov,Alan C. Evans,Kelly N. Botteron,C. Robert Almli,Robert C. McKinstry,D. Louis Collins +5 more
TL;DR: The methods used to create unbiased, age-appropriate MRI atlas templates for pediatric studies that represent the average anatomy for the age range of 4.5-18.5 years are presented, while maintaining a high level of anatomical detail and contrast.
Journal ArticleDOI
Unbiased diffeomorphic atlas construction for computational anatomy.
TL;DR: A new method for unbiased construction of atlases in the large deformation diffeomorphic setting in the child neuroimaging autism study is described and the segmentation of new subjects via atlas mapping is demonstrated.
Book ChapterDOI
Symmetric Log-Domain Diffeomorphic Registration: A Demons-Based Approach
TL;DR: In this paper, a non-linear image registration algorithm is proposed for log-Euclidean statistics on diffeomorphisms, which works completely in the log-domain, i.e. it uses a stationary velocity field.
Journal ArticleDOI
The geometric median on Riemannian manifolds with application to robust atlas estimation
TL;DR: This paper extends the notion of robust estimation, a well established and powerful tool in traditional statistical analysis of Euclidian data, to manifold-valued representations of anatomical variability, and presents a robust brain atlas estimation technique based on the geometric median in the space of deformable images.