ArticleBMC bioinformatics2015
Constrained distance transforms for spatial atlas registration.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Integrated analysis of Wnt signalling system component gene expression.Development (Cambridge, England) · 2022Article
- Review
- Emergence of structure in mouse embryos: Structural Entropy morphometry applied to digital models of embryonic anatomy.Journal of anatomy · 2019Article
- eMouseAtlas: An atlas-based resource for understanding mammalian embryogenesis.Developmental biology · 2017Review
- The 'straight mouse': defining anatomical axes in 3D embryo models.Database : the journal of biological databases and curation · 2017Article
- Representation of anatomy in online atlases and databases: a survey and collection of patterns for interface design.BMC developmental biology · 2016Article
- eMouseAtlas informatics: embryo atlas and gene expression database.Mammalian genome : official journal of the International Mammalian Genome Society · 2015Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
backgroundSpatial frameworks are used to capture organ or whole organism image data in biomedical research. The registration of large biomedical volumetric images is a complex and challenging task, but one that is required for spatially mapped biomedical atlas systems. In most biomedical applications the transforms required are non-rigid and may involve significant deformation relating to variation in pose, natural variation and mutation. Here we develop a new technique to establish such transformations for mapping data that cannot be achieved by existing approaches and that can be used interactively for expert editorial review.
resultsThis paper presents the Constrained Distance Transform (CDT), a novel method for interactive image registration. The CDT uses radial basis function transforms with distances constrained to geodesics within the domains of the objects being registered. A geodesic distance algorithm is discussed and evaluated. Examples of registration using the CDT are presented.
conclusionThe CDT method is shown to be capable of simultaneous registration and foreground segmentation even when very large deformations are required.
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