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A highly accurate quantum optimization algorithm for CT image reconstruction based on sinogram patterns.

Kyungtaek Jun¹

¹Quantum Research Center, QTomo, Busan, South Korea. ktfriends@gmail.com.

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|September 1, 2023

Summary

This study introduces a novel quantum algorithm for reconstructing computed tomography (CT) images, improving clarity by addressing artifacts. The quantum approach enhances image quality for applications in medical imaging and beyond.

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Area of Science:

Medical Imaging
Quantum Computing
Image Reconstruction

Background:

Computed tomography (CT) is a vital non-destructive imaging technique.
Image artifacts and back-projection algorithm limitations hinder photorealistic CT image quality.
Iterative optimization algorithms offer improvements by utilizing entire sinograms.

Purpose of the Study:

Introduce a novel quantum algorithm for CT image reconstruction.
Enhance the clarity and quality of CT images.
Provide a versatile algorithm applicable to various light sources and CT configurations.

Main Methods:

Developed a quantum algorithm expressing CT images as qubit combinations.
Utilized the Radon transform to acquire the projection of the CT image.
Combined experimental sinograms with optimized qubits for reconstruction.
Employed global energy optimization to determine qubit values via quantum computing or annealing.

Main Results:

The proposed quantum algorithm effectively reconstructs CT images.
The method addresses and reduces artifacts common in CT scans.
Demonstrated applicability to cone-beam CT and general medical imaging.

Conclusions:

The new quantum algorithm offers a significant advancement in CT image reconstruction.
This approach has the potential to improve diagnostic accuracy in medical imaging.
The algorithm's flexibility with light sources and CT types broadens its utility.