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Automatic correction of intensity nonuniformity from sparseness of gradient distribution in medical images
Yuanjie Zheng1, Murray Grossman, Suyash P Awate
1Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
Abstract:
We propose to use the sparseness property of the gradient probability distribution to estimate the intensity nonuniformity in medical images, resulting in two novel automatic methods: a non-parametric method and a parametric method. Our methods are easy to implement because they both solve an iteratively re-weighted least squares problem. They are remarkably accurate as shown by our experiments on images of different imaged objects and from different imaging modalities.