Noise modeling and variance stabilization of a computed radiography (CR) mammography system subject to fixed-pattern noise

Autor(es)

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]

Afiliação do(s) autor(es)

^[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

• Tipo de documento: Artigo Científico
• Fonte: Physics in Medicine and Biology; v. 65, n. 22 NOV 21 2020.
• Citações Web of Science: 0

Resumo

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)

• Processo FAPESP: 14/50889-7 - INCT 2014: em Medicina Assistida por Computação Científica (INCT-MACC)
• Beneficiário: José Eduardo Krieger
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 18/19888-5 - Redução da dose de radiação em imagens de radiografia computadorizada (CR) da mama através de processamento de imagens
• Beneficiário: Lucas Rodrigues Borges
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado