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Computed tomography (CT) has been developed as a non-destructive techniquefor observing minute internal images of samples. It has been difficult toobtain photo-realistic (clean or clear) CT images due to various unwantedartifacts generated during the CT scanning process, along with limitations ofback projection algorithms. Recently, an iterative optimization algorithm hasbeen developed that uses the entire sinogram to reduce errors caused byartifacts. In this paper, we introduce a new quantum algorithm forreconstructing CT images. This algorithm can be used with any type of lightsource as long as the projection is defined. Suppose we have an experimentalsinogram produced by a Radon transform. To find the CT image of this sinogram,we express the CT image as a combination of qubits. After the Radon transformof the undetermined CT image, we find the combination of the actual sinogramand the optimized qubits. The global energy optimization value used here candetermine the value of qubits through a gate model quantum computer or quantumannealer. In particular, the new algorithm can also be used for cone-beam CTimage reconstructions and will be of great help in the field of medicalimaging.

Highly accurate quantum optimization algorithm for CT image reconstructions based on sinogram patterns