Scripts and parameters used in my publications
2019
"An efficient preconditioner for stochastic gradient descent optimization of image registration"
In this paper, we propose a new computationally efficient method to automatically estimate a preconditioner for stochastic gradient descent optimization for image registration. This paper compares the proposed method to fast ASGD and other preconditioner estimation methods, using many different datasets of different modality and anatomical structure. The proposed method was validated on different datasets and shows comparable accuracy as the fast ASGD method in the image registration toolbox elastix. It however improves the registration time about >5 times faster in affine registration and >2 times faster in B-spline registration. This improvement is crucial for near real-time registration in high dimensional image registration. More details could be found here.
"Evaluation of an open source registration package for automatic contour propagation in online adaptive intensity-modulated proton therapy of prostate cancer"
This paper investigates the performance of an open source deformable image registration package, elastix, for fast and robust contour propagation in the context of online-adaptive intensity-modulated proton therapy (IMPT) for prostate cancer. Compared to ANTs package, elastix may facilitate online adaptive IMPT of prostate cancer using a fast, free and open implementation. More details could be found here.
"FOD-based registration for susceptibility distortion correction in brainstem connectome imaging" This paper proposed a FOD-based registration method for susceptibility distortion correction. It could correct residual distortions in data preprocessed by HCP Pipeline. More details could be found here.
If you have any questions, please contact me via Yuchuan.Qiao@loni.usc.edu.