Supervised Reconstruction for Silhouette Tomography
<|reference_start|>Supervised Reconstruction for Silhouette Tomography: In this paper, we introduce silhouette tomography, a novel formulation of X-ray computed tomography that relies only on the geometry of the imaging system. We formulate silhouette tomography mathematically and provide a simple method for obtaining a particular solution to the problem, assuming that any solution exists. We then propose a supervised reconstruction approach that uses a deep neural network to solve the silhouette tomography problem. We present experimental results on a synthetic dataset that demonstrate the effectiveness of the proposed method.<|reference_end|>
@article{bell2024supervised,
    title={Supervised Reconstruction for Silhouette Tomography},
    author={Evan Bell, Michael T. McCann, Marc Klasky},
    journal={arXiv preprint arXiv:2402.07298},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.07298},
    primaryClass={eess.IV cs.CV}
}