A Fast Piece-wise Deformable Method for Multi-Modality Image Registration

Gopalakrishnan, Girish; Kumar, Sunil; Narayanan, Ajay; Mullick, Rakesh

doi:10.1109/aipr.2005.7

Cited by 4 publications

(2 citation statements)

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“…This means that certain landmarks which are deemed to be in correspondence in the two images are "pinned" to each other and the remaining parts of the images are stretched to fit amongst these pinned landmarks. The most closely related method of which we are aware, developed for multi-modal image analysis, is from Gopalakrishnan et al [ 12 ], which finds information rich landmarks automatically and uses an approximate local affine (The term affine registration refers to a registration in which one image has undergone an affine transformation . An affine transformation is an image transformation in which straight lines remain straight, and parallel lines remain parallel.…”

Section: Introductionmentioning

confidence: 99%

Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering

et al. 2007

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Background: Many important high throughput projects use in situ hybridization and may require the analysis of images of spatial cross sections of organisms taken with cellular level resolution. Projects creating gene expression atlases at unprecedented scales for the embryonic fruit fly as well as the embryonic and adult mouse already involve the analysis of hundreds of thousands of high resolution experimental images mapping mRNA expression patterns. Challenges include accurate registration of highly deformed tissues, associating cells with known anatomical regions, and identifying groups of genes whose expression is coordinately regulated with respect to both concentration and spatial location. Solutions to these and other challenges will lead to a richer understanding of the complex system aspects of gene regulation in heterogeneous tissue.

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Section: Introductionmentioning

confidence: 99%

Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering

et al. 2007

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“…In the past, this problem has been addressed using two broad methods: piece-wise rigid and pure deformable. Prior algorithms perform piece-wise registrations [1,2] where the interesting regions within a volume are selected based on structure/feature or intensity. Some algorithms perform a non-rigid registration to obtain the deformation field [3].…”

Section: Introductionmentioning

confidence: 99%