In Medical physics ; h5-index 59.0
BACKGROUND : With the development of low-dose computed tomography (CT), incomplete data reconstruction has been widely concerned. The total variation (TV) minimization algorithm can accurately reconstruct images from sparse or noisy data.
PURPOSE : However, the traditional TV algorithm ignores the direction of structures in images, leading to the loss of edge information and block artifacts when the object is not piecewise constant. Since the anisotropic information can facilitate preserving the edge and detail information in images, we aims to improve the TV algorithm in terms of reconstruction accuracy via this approach.
METHODS : In this paper, we propose an adaptive-weighted high order total variation (awHOTV) algorithm. We construct the second order TV-norm using the second order gradient, adapt the anisotropic edge property between neighboring image pixels, adjust the local image-intensity gradient to keep edge information, and design the corresponding Chambolle-Pock (CP) solving algorithm. Implementing the proposed algorithm, comprehensive studies are conducted in the ideal projection data experiment where the SSIM, RMSE, CNR, and MTF curves are utilized to evaluate the quality of reconstructed images in statism, structure, spatial resolution, and contrast, respectively. In the noisy data experiment, we further use the NPS curve to evaluate the reconstructed images and compare it with other three algorithms.
RESULTS : We use the 2D slice in the XCAT phantom, 2D slice in TCIA Challenge data and FORBILD phantom as simulation phantoms and use real bird data for real verification. The results show that, compared with the traditional TV and FBP algorithms, the awHOTV has better performance in terms of RMSE, SSIM, and PCC under the projected data with different sparsity. In addition, the awHOTV algorithm is robust against the noise of different intensities.
CONCLUSIONS : The proposed awHOTV method can reconstruct the images with high accuracy under sparse or noisy data. The awHOTV solves the strip artifacts caused by sparse data in the FBP method. Compared with the TV method, the awHOTV can effectively suppress block artifacts and has good detail protection ability.
Xi Yarui, Zhou Pengwu, Yu Haijun, Zhang Tao, Zhang Lingli, Qiao Zhiwei, Liu Fenglin
2023-Mar-19
adaptive-weighted high order total variation, chambolle-pock algorithm, compressed sensing, image reconstruction, iterative algorithm
