Near-isotropic super-resolution CBCT imaging with a dual-layer flat panel detector

<i>Background.</i>For medical imaging, usually, it is crucial to have high spatial resolution. Studies have demonstrated that the novel dual-layer flat panel detectors (FPDs) can acquire extra spatial information to enable super-resolution cone beam CT(CBCT) imaging compared to the conventional single-layer FPDs.<i>Objective.</i>The aim of this study is to investigate the feasibility of realizing near-isotropic super-resolution CBCT imaging with a dual-layer flat panel detector.<i>Methods.</i>To retrieve the near-isotropic super-resolution imaging information, a general mathematical signal model that includes the relative shift, namely, Δ<i>u</i>along the horizontal<i>u</i>-axis, Δ<i>v</i>along the vertical<i>v</i>-axis, between the two detector pixel arrays and the gap Δ<i>d</i>between the two detector layers, is established. Afterwards, an recurrent neural network-based deep neural network, named as two-dimensional 2D-suRi-Net, is employed to efficiently retrieve the projections having near-isotropic super-resolution imaging information. Numerical simulations were performed to investigate the impact of the relative shift (Δ<i>u</i>, Δ<i>v</i>) and the gap Δ<i>d</i>under different scenarios. The real performance of this proposed super-resolution CBCT imaging approach is validated by a pig leg specimen and an intersecting cylinder phantom.<i>Results.</i>It is found that introducing half pixel shift, i.e. Δ<i>u</i>= Δ<i>v</i>=0.5δdel(δdeldenotes the pixel dimension), between the two detector layers is necessary for super-resolution CBCT imaging, particularly when the detector gap Δ<i>d</i>is less than 3 mm. Results demonstrate that the proposed 2D-suRi-Net can effectively retrieve higher spatial resolution information from the acquired low-energy and high-energy projections having lower spatial resolution. Quantitatively, the spatial resolution difference between the reconstructed super-resolution CBCT images on the axial and coronal plane is less than 10%, demonstrating the near-isotropic super-resolution imaging capability of the 2D-suRi-Net method.<i>Conclusion.</i>In summary, this study demonstrates the feasibility of near-isotropic super-resolution CBCT imaging for dual-layer FPD based CBCT imaging systems.