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.
@article{arxiv.2006.16120,
title = {Shape from Projections via Differentiable Forward Projector for Computed Tomography},
author = {Jakeoung Koo and Anders B. Dahl and J. Andreas Bærentzen and Qiongyang Chen and Sara Bals and Vedrana A. Dahl},
journal= {arXiv preprint arXiv:2006.16120},
year = {2021}
}