Registration based super-resolution reconstruction for lung 4D-CT image

被引：0

作者：

Wu, Xiu-Xiu ^{[1
]}

Xiao, Shan ^{[1
]}

Zhang, Yu ^{[1
]}

机构：

[1] School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, Guangdong

来源：

Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2015年 / 43卷 / 02期

关键词：

Active Demons registration; Lung 4D-CT data; POCS algorithm; Super-resolution reconstruction;

D O I：

10.3969/j.issn.0372-2112.2015.02.027

中图分类号：

学科分类号：

摘要：

Lung 4D-CT plays an important role in lung cancer radiotherapy. However, due to the great inter-slice thickness, the fuzzy images will be induced because of interpolation operation during the multi-plane display. In this paper, we take the low-resolution images of different phases in the corresponding position as different “frame” images, and propose a registration based super-resolution reconstruction method to improve the resolution of lung 4D-CT images. First, we employ the Active Demons registration to estimate the motion field between different “frames”. Then, the projection onto convex set (POCS) approach is employed to reconstruction high-resolution lung images. The experimental results show that our method can get more clear lung images and significantly enhance image structure, compared with the cubic spline interpolation and back projection method. ©, 2015, Chinese Institute of Electronics. All right reserved.

引用

页码：383 / 386

页数：3

共 9 条

[1]

Khan F., Bell G., Antony J., Palmer M., Balter P., Bucci K., Chapman M.J., The use of 4DCT to reduce lung dose: A dosimetric analysis, Medical Dosimetry, 34, 4, pp. 273-278, (2010)

[2]

Li T., Schreibmann E., Thorndyke B., Tillman G., Boyer A., Koong A., Goodman K., Xing L., Radiation dose reduction in four-dimensional computed tomography, Medical Physics, 32, 12, pp. 3650-3660, (2005)

[3]

Thirion J.P., Image matching as diffusion process: an analogy with Maxwell's demons, Medical Image Analysis, 2, 3, pp. 243-260, (1998)

[4]

Wang H., Dong L., Validation of an accelerated “demons” algorithm for deformable image registration in radiation therapy, Physics in Medicine Biology, 50, 12, pp. 2887-2905, (2005)

[5]

Han Y.-B., Chen X.-Q., Wu L.-N., A superresolution reconstruction algorithm of video sequence, Acta Electronica Sinica, 33, 1, pp. 126-130, (2005)

[6]

Shao W.-Z., Wei Z.-H., Multi-frame super-resolution reconstruction based on anisotropic markov random field modeling, Acta Electronica Sinica, 36, 6, pp. 1256-1263, (2009)

[7]

Li D.-P., Yu W.-J., The improved POCS algorithm based on edge optimization, Modern Computer (Professional edition), 18, pp. 21-26, (2013)

[8]

Castillo R., Castillo E., Guerra R., Johnson V.E., Mcphail T., Garg A.K., Guerrero T., A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets, Physics in Medicine and Biology, 54, 7, pp. 1849-1870, (2009)

[9]

Xu M.-F., Liu J.-H., Super-resolution image reconstruction of aerial photography based on projection onto convex sets, Chinese Journal of Liquid Crystals and Displays, 25, 6, pp. 873-878, (2010)

← 1 →