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Nonrigid Registration Regularized by Shape Information: Application to Atlas Construction of Cardiac CT Images.

Zha Y, Lu X, Wang L, Yang R, Ou S, Xing D, Wang D - PLoS ONE (2015)

Bottom Line: For one thing, the multiscale gradient orientation features of images are combined to form the construction of multifeature mutual information.Additionally, the shape information of multiple-objects in images is incorporated into the cost function for registration.The obtained atlas can represent the cardiac structures more accurately.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, P. R. China.

ABSTRACT
Cardiac atlases play an important role in the computer-aided diagnosis of cardiovascular diseases, in particular they need to deal with large and highly variable image datasets. In this paper, we propose a new nonrigid registration algorithm incorporating shape information, to produce comprehensive atlases. For one thing, the multiscale gradient orientation features of images are combined to form the construction of multifeature mutual information. Additionally, the shape information of multiple-objects in images is incorporated into the cost function for registration. We demonstrate the merits of the new registration algorithm on the 3D data sets of 15 patients. The experimental results show that the new registration algorithm can outperform the conventional intensity-based registration method. The obtained atlas can represent the cardiac structures more accurately.

No MeSH data available.


Related in: MedlinePlus

Two views of atlas mesh corresponding to the synthesized mean image.Different colors indicate different structures.
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pone.0130730.g006: Two views of atlas mesh corresponding to the synthesized mean image.Different colors indicate different structures.

Mentions: In Fig 5, a typical example of the registration result using MI (c) and our method (d) is illustrated. The LA and LVM of the fixed (a) and moving (b) image are very different. It can be observed that our method can achieve better alignment with the reference image than using the MI method. Fig 6 shows two views of the atlas mesh, corresponding to the synthesized mean image by registration. They can clearly display the six structures of cardiac images.


Nonrigid Registration Regularized by Shape Information: Application to Atlas Construction of Cardiac CT Images.

Zha Y, Lu X, Wang L, Yang R, Ou S, Xing D, Wang D - PLoS ONE (2015)

Two views of atlas mesh corresponding to the synthesized mean image.Different colors indicate different structures.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4482436&req=5

pone.0130730.g006: Two views of atlas mesh corresponding to the synthesized mean image.Different colors indicate different structures.
Mentions: In Fig 5, a typical example of the registration result using MI (c) and our method (d) is illustrated. The LA and LVM of the fixed (a) and moving (b) image are very different. It can be observed that our method can achieve better alignment with the reference image than using the MI method. Fig 6 shows two views of the atlas mesh, corresponding to the synthesized mean image by registration. They can clearly display the six structures of cardiac images.

Bottom Line: For one thing, the multiscale gradient orientation features of images are combined to form the construction of multifeature mutual information.Additionally, the shape information of multiple-objects in images is incorporated into the cost function for registration.The obtained atlas can represent the cardiac structures more accurately.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, P. R. China.

ABSTRACT
Cardiac atlases play an important role in the computer-aided diagnosis of cardiovascular diseases, in particular they need to deal with large and highly variable image datasets. In this paper, we propose a new nonrigid registration algorithm incorporating shape information, to produce comprehensive atlases. For one thing, the multiscale gradient orientation features of images are combined to form the construction of multifeature mutual information. Additionally, the shape information of multiple-objects in images is incorporated into the cost function for registration. We demonstrate the merits of the new registration algorithm on the 3D data sets of 15 patients. The experimental results show that the new registration algorithm can outperform the conventional intensity-based registration method. The obtained atlas can represent the cardiac structures more accurately.

No MeSH data available.


Related in: MedlinePlus