3-D Reconstruction in Canonical Co-Ordinate Space From Arbitrarily Oriented 2-D Images

@article{Hou20173DRI,
  title={3-D Reconstruction in Canonical Co-Ordinate Space From Arbitrarily Oriented 2-D Images},
  author={Benjamin Hou and B. Khanal and Amir Alansary and Steven G. McDonagh and Alice Davidson and Mary A. Rutherford and Joseph V. Hajnal and Daniel Rueckert and Ben Glocker and Bernhard Kainz},
  journal={IEEE Transactions on Medical Imaging},
  year={2017},
  volume={37},
  pages={1737-1750}
}
Limited capture range, and the requirement to provide high quality initialization for optimization-based 2-D/3-D image registration methods, can significantly degrade the performance of 3-D image reconstruction and motion compensation pipelines. Challenging clinical imaging scenarios, which contain significant subject motion, such as fetal in-utero imaging, complicate the 3-D image and volume reconstruction process. In this paper, we present a learning-based image registration method capable of… 

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