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A novel digital tomosynthesis (DTS) reconstruction method using a deformation field map.

机译:一种使用变形场图的新型数字断层合成(DTS)重建方法。

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We developed a novel digital tomosynthesis (DTS) reconstruction method using a deformation field map to optimally estimate volumetric information in DTS images. The deformation field map is solved by using prior information, a deformation model, and new projection data. Patients' previous cone-beam CT (CBCT) or planning CT data are used as the prior information, and the new patient volume to be reconstructed is considered as a deformation of the prior patient volume. The deformation field is solved by minimizing bending energy and maintaining new projection data fidelity using a nonlinear conjugate gradient method. The new patient DTS volume is then obtained by deforming the prior patient CBCT or CT volume according to the solution to the deformation field. This method is novel because it is the first method to combine deformable registration with limited angle image reconstruction. The method was tested in 2D cases using simulated projections of a Shepp-Logan phantom, liver, and head-and-neck patient data. The accuracy of the reconstruction was evaluated by comparing both organ volume and pixel value differences between DTS and CBCT images. In the Shepp-Logan phantom study, the reconstructed pixel signal-to-noise ratio (PSNR) for the 60 degrees DTS image reached 34.3 dB. In the liver patient study, the relative error of the liver volume reconstructed using 60 degrees projections was 3.4%. The reconstructed PSNR for the 60 degrees DTS image reached 23.5 dB. In the head-and-neck patient study, the new method using 60 degrees projections was able to reconstruct the 8.1 degrees rotation of the bony structure with 0.0 degrees error. The reconstructed PSNR for the 60 degrees DTS image reached 24.2 dB. In summary, the new reconstruction method can optimally estimate the volumetric information in DTS images using 60 degrees projections. Preliminary validation of the algorithm showed that it is both technically and clinically feasible for image guidance in radiation therapy.
机译:我们开发了一种新颖的数字层析合成(DTS)重建方法,该方法使用变形场图来最佳估计DTS图像中的体积信息。通过使用先验信息,变形模型和新的投影数据来求解变形场图。将患者先前的锥形束CT(CBCT)或计划的CT数据用作先验信息,并将要重建的新患者体积视为先前患者体积的变形。通过使用非线性共轭梯度法最小化弯曲能并保持新的投影数据保真度来解决变形场。然后,通过根据变形场的解来使先前的患者CBCT或CT体积变形来获得新的患者DTS体积。该方法是新颖的,因为它是将可变形配准与有限角度图像重建相结合的第一种方法。该方法已在2D情况下使用Shepp-Logan幻像,肝脏和头颈部患者数据的模拟投影进行了测试。通过比较DTS和CBCT图像之间的器官体积和像素值差异来评估重建的准确性。在Shepp-Logan幻象研究中,针对60度DTS图像的重建像素信噪比(PSNR)达到34.3 dB。在肝脏患者研究中,使用60度投影重建的肝脏体积的相对误差为3.4%。 60度DTS图像的重建PSNR达到23.5 dB。在头颈部患者研究中,使用60度投影的新方法能够以0.0度的误差重建骨骼结构的8.1度旋转。 60度DTS图像的重建PSNR达到24.2 dB。总之,新的重建方法可以使用60度投影来最佳估计DTS图像中的体积信息。该算法的初步验证表明,在放射治疗中进行图像引导在技术上和临床上都是可行的。

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