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Maximum entropy co-processor for computed tomography

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3 Author(s)
Chang, S. ; Dept. of Defense, Fort Meade, MD, USA ; Peckerar, M. ; Marrian, Christie

In this paper, we present a neural net co-processor capable of performing computed tomographic image reconstruction. The circuit performs the Radon transformation using a cost function gradient descent method. The unique aspect of this co-processor is the incorporation of informational entropy as a regularizer in the optimization problem. A 10 pixel×10 pixel array was designed and fabricated in 2 μm CMOS technology. Convergence time of the array was less than 5 μs. Issues relating to scaling the array to larger sizes are discussed in this paper

Published in:

Custom Integrated Circuits Conference, 1994., Proceedings of the IEEE 1994

Date of Conference:

1-4 May 1994