تقرير
POLAFFINI: Efficient feature-based polyaffine initialization for improved non-linear image registration
| العنوان: | POLAFFINI: Efficient feature-based polyaffine initialization for improved non-linear image registration |
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| المؤلفون: | Legouhy, Antoine, Callaghan, Ross, Azadbakht, Hojjat, Zhang, Hui |
| المصدر: | Information Processing in Medical Imaging. IPMI 2023. Lecture Notes in Computer Science, vol 13939. Springer, Cham |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | This paper presents an efficient feature-based approach to initialize non-linear image registration. Today, nonlinear image registration is dominated by methods relying on intensity-based similarity measures. A good estimate of the initial transformation is essential, both for traditional iterative algorithms and for recent one-shot deep learning (DL)-based alternatives. The established approach to estimate this starting point is to perform affine registration, but this may be insufficient due to its parsimonious, global, and non-bending nature. We propose an improved initialization method that takes advantage of recent advances in DL-based segmentation techniques able to instantly estimate fine-grained regional delineations with state-of-the-art accuracies. Those segmentations are used to produce local, anatomically grounded, feature-based affine matchings using iteration-free closed-form expressions. Estimated local affine transformations are then fused, with the log-Euclidean polyaffine framework, into an overall dense diffeomorphic transformation. We show that, compared to its affine counterpart, the proposed initialization leads to significantly better alignment for both traditional and DL-based non-linear registration algorithms. The proposed approach is also more robust and significantly faster than commonly used affine registration algorithms such as FSL FLIRT. Comment: submitted and accepted to IPMI 2023 |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1007/978-3-031-34048-2_47 |
| URL الوصول: | http://arxiv.org/abs/2407.03922 |
| رقم الأكسشن: | edsarx.2407.03922 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1007/978-3-031-34048-2_47 |
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