量子算法让断层成像更快更准，少一半数据也能清晰成像。
Quantum Supremacy in Tomographic Imaging: Advances in Quantum Tomography Algorithms
- 用量子优化算法降低断层扫描所需投影角度
- 仅用50%角度即可准确重建，且抗50%数据误差
- 适合医疗影像与材料科学等高精度成像场景
量子计算作为变革性范式，可在实际时间内解决经典方法无法处理的复杂问题。在断层成像重建中，量子优化算法实现更快处理与更清晰成像。本研究进一步验证了量子优势：在保持高质量重建的同时，显著减少所需投影角度，并提升对图像伪影的鲁棒性。实验表明，即使在正弦图中引入高达50%的误差以模拟环形伪影，所提算法仍能无伪影地准确重建图像；同时仅需原0°至180°范围内50%的投影角度即可实现精确重构。这些结果展示了量子算法在高效、高精度断层成像中的潜力，为医学影像、材料科学及先进断层系统应用铺平道路，随着量子计算技术进步，其应用前景广阔。
原文摘要 · Abstract (English)
Quantum computing has emerged as a transformative paradigm, capable of tackling complex computational problems that are infeasible for classical methods within a practical timeframe. At the core of this advancement lies the concept of quantum supremacy, which signifies the ability of quantum processors to surpass classical systems in specific tasks. In the context of tomographic image reconstruction, quantum optimization algorithms enable faster processing and clearer imaging than conventional methods. This study further substantiates quantum supremacy by reducing the required projection angles for tomographic reconstruction while enhancing robustness against image artifacts. Notably, our experiments demonstrated that the proposed algorithm accurately reconstructed tomographic images without artifacts, even when up to 50% error was introduced into the sinogram to induce ring artifacts. Furthermore, it achieved precise reconstructions using only 50% of the projection angles from the original sinogram spanning 0° to 180°. These findings highlight the potential of quantum algorithms to revolutionize tomographic imaging by enabling efficient and accurate reconstructions under challenging conditions, paving the way for broader applications in medical imaging, material science, and advanced tomography systems as quantum computing technologies continue to advance.
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