Brain Hallucination

Abstract

In this paper, we investigate brain hallucination, or generating a high resolution brain image from an input low-resolution image, with the help of another high resolution brain image. Contrary to interpolation techniques, the reconstruction process is based on a physical model of image acquisition. Our contribution is a new regularization approach that uses an example-based framework integrating non-local similarity constraints to handle in a better way repetitive structures and texture. The effectiveness of our approach is demonstrated by experiments on realistic Magnetic Resonance brain images generating automatically high-quality hallucinated brain images from low-resolution input.