| Full text | |
| Author(s): |
Borges, Lucas R.
[1]
;
Brochi, Marco A. C.
[1]
;
Xu, Zhongwei
[2]
;
Foi, Alessandro
[3]
;
Vieira, Marcelo A. C.
[4]
;
Azevedo-Marques, Paulo M.
[1]
Total Authors: 6
|
| Affiliation: | [1] Univ Sao Paulo, Ribeirao Preto Med Sch, Sao Paulo - Brazil
[2] Noiseless Imaging Ltd, Tampere - Finland
[3] Tampere Univ, Tampere - Finland
[4] Univ Sao Paulo, Sao Carlos Sch Engn, Sao Paulo - Brazil
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | Physics in Medicine and Biology; v. 65, n. 22 NOV 21 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
In this work we model the noise properties of a computed radiography (CR) mammography system by adding an extra degree of freedom to a well-established noise model, and derive a variance-stabilizing transform (VST) to convert the signal-dependent noise into approximately signal-independent. The proposed model relies on a quadratic variance function, which considers fixed-pattern (structural), quantum and electronic noise. It also accounts for the spatial-dependency of the noise by assuming a space-variant quantum coefficient. The proposed noise model was compared against two alternative models commonly found in the literature. The first alternative model ignores the spatial-variability of the quantum noise, and the second model assumes negligible structural noise. We also derive a VST to convert noisy observations contaminated by the proposed noise model into observations with approximately Gaussian noise and constant variance equals to one. Finally, we estimated a look-up table that can be used as an inverse transform in denoising applications. A phantom study was conducted to validate the noise model, VST and inverse VST. The results show that the space-variant signal-dependent quadratic noise model is appropriate to describe noise in this CR mammography system (errors< 2.0% in terms of signal-to-noise ratio). The two alternative noise models were outperformed by the proposed model (errors as high as 14.7% and 9.4%). The designed VST was able to stabilize the noise so that it has variance approximately equal to one (errors< 4.1%), while the two alternative models achieved errors as high as 26.9% and 18.0%, respectively. Finally, the proposed inverse transform was capable of returning the signal to the original signal range with virtually no bias. (AU) | |
| FAPESP's process: | 14/50889-7 - National Institute of Science and Technology Medicine Assisted by Scientific Computing (INCT-MACC) |
| Grantee: | José Eduardo Krieger |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 18/19888-5 - Radiation dose reduction in computed radiography (CR) mammography through image processing |
| Grantee: | Lucas Rodrigues Borges |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |