In this paper, we present our approach to the 3D CBCT Challenge 2024, a part of ICASSP SP Grand Challenges 2024. Improvement in Cone Beam Computed Tomography (CBCT) reconstruction has been achieved by integrating Swin Image Restoration (SwinIR) based sinogram and image enhancement modules. The proposed methodology uses Nesterov Accelerated Gradient Descent (NAG) to solve the least squares (NAG-LS) problem in CT image reconstruction. The integration of sinogram and image enhancement modules aims to enhance image clarity and preserve fine details, offering a promising solution for both low dose and clinical dose CBCT reconstruction. The averaged mean squared error (MSE) over the validation dataset has decreased significantly, in the case of low dose by one-fifth and clinical dose by one-tenth. Our solution is one of the top 5 approaches in this challenge.

翻译：本文介绍了我们在2024年ICASSP SP大挑战赛之3D CBCT挑战赛中的研究方法。通过集成基于Swin图像修复（SwinIR）的正弦图增强模块与图像增强模块，实现了锥束计算机断层扫描（CBCT）重建性能的提升。所提出的方法采用涅斯捷罗夫加速梯度下降（NAG）求解CT图像重建中的最小二乘（NAG-LS）问题。正弦图与图像增强模块的集成旨在提升图像清晰度并保留精细细节，为低剂量与临床剂量CBCT重建提供了有前景的解决方案。验证数据集上的平均均方误差（MSE）显著降低，低剂量场景下降低至五分之一，临床剂量场景下降低至十分之一。我们的解决方案在该挑战赛中位列前五。