Conventional computed tomography relies on solid-state scintillator Energy-Integrating Detectors (EIDs) that sum total deposited X-ray energy across a polychromatic beam, collapsing spectral material signatures into a single ambiguous grayscale Hounsfield Unit (HU) while adding thermal electronic dark noise and requiring elevated patient radiation doses (8.0–12.0 mSv). To transform diagnostic radiology into an ultra-low-dose, quantitative "true-color" imaging modality—realizing the clinical ideal of a "Magic Camera (PCCT)" (体の中をカラーで撮影する「まほうのカメラ」) that visualizes internal human anatomy in vivid material-specific color at minimal radiation exposure—this monograph formalizes the Photon-Counting Computed Tomography Protocol 2.0 (PCCT-P2.0) architecture. By coupling direct-conversion wide-bandgap semiconductor detectors (CdTe/CdZnTe and deep-silicon arrays) across B = 6 hardware energy-discriminator thresholds with a bedside Google Android Edge-Tensor compute node, PCCT-P2.0 completely eliminates electronic dark noise (η_elec = 0), achieves 0.15 mm isotropic ultra-high-resolution (UHR) spatial acuity, and reduces effective radiation dose by 75%–85% (D_eff in [0.45, 0.85] mSv). Using Primal-Dual Total Nuclear Variation with Physics-Informed K-Edge Basis Decomposition (PD-TNV-K-Edge) accelerated on Android Tensor/NPU silicon via Vulkan Compute, PCCT-P2.0 separates photoelectric, Compton, water, calcium, lipid, and K-edge contrast agents (iodine at 33.17 keV, gadolinium at 50.24 keV) into quantitative color-coded density maps within 6.8 seconds. Every spectral inversion step is arithmetized inside the QFS-zkVM over the 64-bit Goldilocks prime field F_p (p = 2^64 - 2^32 + 1), routed via PHOENIX_BRIDGE / PHOENIX_ROUTER, and governed by Q-SAFA post-quantum lattice cryptography and a Human-in-Command (HIC) hardware interlock satisfying analogous SEC Rule 15c3-5 pre-emission dose ceilings and Delaware Caremark fiduciary safety oversight mandates. Governed by Creative Commons Attribution 4.0 International (CC BY 4.0) with Strict No-Learn Covenant (NLL-v1.0-2026).
No takes yet. Share an insight, caveat, or question.
Yoko(洋子) Hasebe(長谷部) (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: