%0 Journal Article %1 Beg_2004_1167 %A Beg, Mirza Faisal %A Helm, Patrick A %A McVeigh, Elliot %A Miller, Michael I %A Winslow, Raimond L %D 2004 %J Magn. Reson. Med. %K 15508155 Algorithms, Animals, Biology, Computational Computer-Assisted, Diffusion Diseases, Dogs, Gov't, Heart Heart, Image Imaging, Magnetic Male, Models, Non-U.S. P.H.S., Processing, Reference Research Resonance Support, Theoretical, U.S. Values, %N 5 %P 1167--1174 %R 10.1002/mrm.20255 %T Computational cardiac anatomy using MRI. %U http://dx.doi.org/10.1002/mrm.20255 %V 52 %X Ventricular geometry and fiber orientation may undergo global or local remodeling in cardiac disease. However, there are as yet no mathematical and computational methods for quantifying variation of geometry and fiber orientation or the nature of their remodeling in disease. Toward this goal, a landmark and image intensity-based large deformation diffeomorphic metric mapping (LDDMM) method to transform heart geometry into common coordinates for quantification of shape and form was developed. Two automated landmark placement methods for modeling tissue deformations expected in different cardiac pathologies are presented. The transformations, computed using the combined use of landmarks and image intensities, yields high-registration accuracy of heart anatomies even in the presence of significant variation of cardiac shape and form. Once heart anatomies have been registered, properties of tissue geometry and cardiac fiber orientation in corresponding regions of different hearts may be quantified.

@article{Beg_2004_1167, abstract = {Ventricular geometry and fiber orientation may undergo global or local remodeling in cardiac disease. However, there are as yet no mathematical and computational methods for quantifying variation of geometry and fiber orientation or the nature of their remodeling in disease. Toward this goal, a landmark and image intensity-based large deformation diffeomorphic metric mapping ({LDDMM}) method to transform heart geometry into common coordinates for quantification of shape and form was developed. Two automated landmark placement methods for modeling tissue deformations expected in different cardiac pathologies are presented. The transformations, computed using the combined use of landmarks and image intensities, yields high-registration accuracy of heart anatomies even in the presence of significant variation of cardiac shape and form. Once heart anatomies have been registered, properties of tissue geometry and cardiac fiber orientation in corresponding regions of different hearts may be quantified.}, added-at = {2009-06-03T11:20:58.000+0200}, author = {Beg, Mirza Faisal and Helm, Patrick A and McVeigh, Elliot and Miller, Michael I and Winslow, Raimond L}, biburl = {https://www.bibsonomy.org/bibtex/2af05ae75a5dbb6bdd02920726b42f1a2/hake}, description = {The whole bibliography file I use.}, doi = {10.1002/mrm.20255}, file = {Beg_2004_1167.pdf:Beg_2004_1167.pdf:PDF}, interhash = {d610512a4e042ebcbf86cc749123ef1a}, intrahash = {af05ae75a5dbb6bdd02920726b42f1a2}, journal = {Magn. Reson. Med.}, keywords = {15508155 Algorithms, Animals, Biology, Computational Computer-Assisted, Diffusion Diseases, Dogs, Gov't, Heart Heart, Image Imaging, Magnetic Male, Models, Non-U.S. P.H.S., Processing, Reference Research Resonance Support, Theoretical, U.S. Values,}, month = Nov, number = 5, pages = {1167--1174}, pmid = {15508155}, timestamp = {2009-06-03T11:21:02.000+0200}, title = {Computational cardiac anatomy using {MRI}.}, url = {http://dx.doi.org/10.1002/mrm.20255}, volume = 52, year = 2004 }