Hierarchical dictionary compressive sensing (HDCS) method in microwave induced thermal acoustic tomography

Abstract Aiming to reduce the reconstruction time and enhance the image quality of microwave induced thermal acoustic tomography (MITAT), a new image reconstruction method named HDCS-MITAT (HDCS: hierarchical dictionary compressive sensing) is proposed. Different from the recently demonstrated CS-MITAT (CS: compressive sensing) imaging method in which only one level dictionary is applied, hierarchical dictionaries are used in the HDCS-MITAT. In this method, the dictionaries with different spatial resolutions are constructed which constitute a hierarchical structure. During the image reconstructions, first the coarsest level dictionary is utilized to roughly estimate the position of the targets in the original image domain. A reduced interested image domain can be set based on this estimation. Then the next level dictionary which has higher resolution than the above level is applied to further estimating the position of the targets and so on. Finally, the finest level dictionary is used to reconstruct the image of the targets. Compared with the CS-MITAT, this HDCS-MITAT has much less computational time and better image quality. The effectiveness of the method has been validated through some simulations and real breast tumor experiments.

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