Back to Search
Start Over
Restarted primal–dual Newton conjugate gradient method for enhanced spatial resolution of reconstructed cone-beam x-ray luminescence computed tomography images
- Source :
- Phys Med Biol
- Publication Year :
- 2020
-
Abstract
- Cone-beam x-ray luminescence computed tomography (CB-XLCT) has been proposed as a promising imaging tool, which enables three-dimensional imaging of the distribution of nanophosphors (NPs) in small animals. However, the reconstruction performance is usually unsatisfactory in terms of spatial resolution due to the ill-posedness of the CB-XLCT inverse problem. To alleviate this problem and to achieve high spatial resolution, a reconstruction method consisting of inner and outer iterations based on a restarted strategy is proposed. In this method, the primal-dual Newton conjugate gradient method (pdNCG) is adopted in the inner iterations to get fast reconstruction, which is used for resetting the permission region and increasing the convergence speed of the outer iteration. To assess the performance of the method, both numerical simulation and physical phantom experiments were conducted with a CB-XLCT system. The results demonstrate that compared with conventional reconstruction methods, the proposed re-pdNCG method can accurately and efficiently resolve the adjacent NPs with the least relative error.
- Subjects :
- Physics
Cone beam computed tomography
Luminescence
Radiological and Ultrasound Technology
Phantoms, Imaging
Image processing
Inverse problem
Cone-Beam Computed Tomography
Signal-To-Noise Ratio
Imaging phantom
Article
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
Signal-to-noise ratio
Approximation error
030220 oncology & carcinogenesis
Conjugate gradient method
Image Processing, Computer-Assisted
Radiology, Nuclear Medicine and imaging
Image resolution
Algorithm
Algorithms
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Phys Med Biol
- Accession number :
- edsair.doi.dedup.....f75f12c29ed223c650e3470126338e55