Estimating the 4D Respiratory Lung Motion by Spatiotemporal Registration and Building Super-Resolution Image

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Summary

A unified approach to estimate the respiratory lung motion with two iterative steps using a new spatiotemporal registration algorithm to align all phase images of 4D-CT onto a high-resolution group-mean image in the common space and achieves more accurate and consistent results in lung motion estimation than all other state-of-the-art approaches.

Type
article
Published
2011-09-18
Cited by
21
References
10

Keywords

Computer science, Artificial intelligence, Computer vision, Image registration, Motion estimation

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