Learning Statistical Correlation of Prostate Deformations for Fast Registration

@article{Shi2011LearningSC,
  title={Learning Statistical Correlation of Prostate Deformations for Fast Registration},
  author={Yonghong Shi and Shu Liao and Dinggang Shen},
  journal={Machine learning in medical imaging. MLMI},
  year={2011},
  volume={7009},
  pages={1-9}
}
This paper presents a novel fast registration method for aligning the planning image onto each treatment image of a patient for adaptive radiation therapy of the prostate cancer. Specifically, an online correspondence interpolation method is presented to learn the statistical correlation of the deformations between prostate boundary and non-boundary regions from a population of training patients, as well as from the online-collected treatment images of the same patient. With this learned… CONTINUE READING