Shape from Projections via Differentiable Forward Projector for Computed Tomography
| Autor: | Koo, Jakeoung, Dahl, Anders B., Bærentzen, J. Andreas, Chen, Qiongyang, Bals, Sara, Dahl, Vedrana A. |
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| Rok vydání: | 2020 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1016/j.ultramic.2021.113239 |
| Popis: | In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data. Comment: Accepted in Ultramicroscopy |
| Databáze: | arXiv |
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