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Abstract #1347

A Constrained Least Squares Approach to MR Image Fusion

Nicholas Dwork1, John M. Pauly1, and Jorge Balbas2

1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Mathematics, California State University in Northridge, Northridge, CA, United States

Fusing a lower resolution color image with a higher resolution monochrome image is a common practice in medical imaging. By incorporating spatial context and/or improving the Signal-to-Noise ratio, the fused image provides clinicians with a single frame of the most complete diagnostic information. In this paper, image fusion is formulated as a convex optimization problem which avoids image decomposition and permits operations at the pixel level. This results in a highly efficient and embarrassingly parallelizable algorithm based on widely available robust and simple numerical methods that realizes the fused image as the global minimizer of the convex optimization problem.

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