Supervised Reconstruction for Silhouette Tomography

Evan Bell, Michael T. McCann, Marc Louis Klasky

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.

External IDs:dblp:journals/corr/abs-2402-07298