Abstract
Registration of Magnetic Resonance Imaging (MRI) scans containing pathologies is challenging due to tissue appearance changes, and still an unsolved problem. In this paper, we present our implementation of the Quadratic Penalty Deformable Image Registration (QPDIR) algorithm for the Brain Tumor Sequence Registration (BraTS-Reg) Challenge 2022. The QPDIR algorithm is an intensity-based algorithm which turns computation of deformation field to an optimization problem of minimizing terms of image dissimilarity and regularization. The terms are computed based on processing exhaustive search among image blocks and the optimization is performed using a gradient-free quadratic penalty method. The whole optimization problem is decomposed to several sub-problems and each of them can be solved by straightforward block coordinate decent iteration. The data set of the BraTS-Reg Challenge 2022 has 160 cases. For each case, pre-operative images and follow-up images of 4 different modalities including t1, t1ce, flair and t2 are provided. For each case, we apply QPDIR to register image pairs of each modality to produce the deformation field, and then add the deformation field to landmarks, and merge the predict landmarks of each modality together to compute the final predict landmarks of the case. During the validation phrase, our method produces the average median absolute error(MAE) of 4.425, the average Robustness of 0.734 and the average negative numbers of Jacobi Determinant of 87960.95. The testing phase rank of our method is at 7. Detailed study of case ID 142 are shown in the paper.
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Acknowledgment
This research was partially supported by National Science Foundation under Grant 2015254. We thank our colleague Yaying Shi for providing comments about using ML/DL methods for this task. We appreciate Dr. Edward Castillo for sharing his idea with us, and we thank the reviewers for their insights.
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Yan, K., Yan, Y. (2023). Applying Quadratic Penalty Method for Intensity-Based Deformable Image Registration on BraTS-Reg Challenge 2022. In: Bakas, S., et al. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2022. Lecture Notes in Computer Science, vol 14092. Springer, Cham. https://doi.org/10.1007/978-3-031-44153-0_1
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