Image Reconstruction of Multiple Basis Materials With Data Augmentation in DECT

基于数据增强的双能CT多基材料图像重建

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Abstract

OBJECTIVE: The objective of the work is to develop algorithms for accurate and stable reconstruction of multiple basis images and virtual monochromatic images (VMIs) in dual-energy CT (DECT). METHODS: The reconstruction task remains challenging in DECT imaging cases with basis regions containing up to 3 basis materials, because the number of voxel values, i.e., unknowns, within the basis regions can be considerably larger than the number of measurements. We exploit the volume-conservation (VC) constraint to augment data and develop an optimization-based algorithm for accurate and stable reconstruction of multiple basis images and VMIs in the cases. RESULTS: Numerical studies are conducted involving simulated and real data for the cases with basis regions containing up to 3 basis materials; and the study result reveals that the algorithm developed can accurately and stably reconstruct multiple basis images and VMIs in DECT. CONCLUSIONS: The exploitation of the VC constraint enables the algorithm proposed for accurately and stably reconstructing multiple basis images in DECT. SIGNIFICANCE: The work reveals that it is possible to obtain accurate VMIs and contrast-concentration estimations in DECT with basis regions containing up to 3 basis materials. The algorithm can be extended for obtaining multiple basis images in photon-counting CT and also be applied to dual-energy data collected only over limited-angular range and/or at sparse views.

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