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Data-driven deformation correction in X-ray spectro-tomography with implicit neural networks
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DOI：10.1016/j.patter.2026.101515.png)
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Abstract
En 中文
• CANet is a self-supervised method correcting X-ray spectro-tomography deformations • Coordinate-based network models continuous deformation for precise image alignment • The method unifies tomographic and spectral alignment in a single framework • Robust alignment enables high-fidelity structural and chemical imaging contrast
Keywords:
X-ray spectro-tomography
deformation correction
self-supervised learning
coordinate-based neural network
implicit neural representations
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