Method for compressed sensing image reconstruction using a priori knowledge of spatial support

Abstract

A method for image reconstruction that utilizes the benefits of compressed sensing (“CS”) while incorporating a priori knowledge of object spatial support into the image reconstruction is provided. Image data is acquired from a subject, for example, with a medical imaging system, such as a magnetic resonance imaging (“MRI”) system or a computed tomography (“CT”) system. An estimate of the spatial support of the subject is produced, for example, using a low resolution image of the subject, or an image reconstructed from undersampled image data in a traditional sense. An estimate image of the subject is also produced by using traditional image reconstruction methods on the acquired image data. An image of the subject is then reconstructed using the produced estimate image and produced spatial support estimate. This method allows for the reconstruction of quality images from undersampled image data in a computationally efficient manner.

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