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Synchrotron radiation (SR) is an excellent light source for micro-CT (micro-computed tomography) applications due to its monochromaticity and high brightness, which are crucial for achieving high-resolution imaging. However, when scanning larger objects, the limited field of view (FOV) of SR will lead to data truncation, limiting its utilization efficiency. To address this limitation, this paper proposed a method to integrate conventional X-ray CT data to supplement the truncated SR data for joint reconstruction to improve imaging. We first employ a polynomial transformation to match the image gray levels from the two distinct light sources and then resample these to form joint data. Subsequently, the method derives noise images from the noise characteristics of the projection data to construct image weight constraint that accurately reflects different data quality from two sources. The flexibility of the image weight constraint also allows for its combination with various denoisers to further enhance the reconstruction quality. Experimental results demonstrate that the proposed method can leverage the strengths of both imaging modalities to facilitate larger scale and high-resolution imaging.
Cao et al. (Thu,) studied this question.