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arXiv · 2402.07298

Supervised Reconstruction for Silhouette Tomography

Evan Bell·Michael T. McCann·Marc Klasky
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Abstract

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.

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Evan Bell, Michael T. McCann, Marc Klasky. 2024-02-11. Supervised Reconstruction for Silhouette Tomography. https://arxiv.org/abs/2402.07298

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