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Improved phase‐attenuation duality method with space‐frequency joint domain iterative regularization
Author(s) -
Zhou Zhongxing,
Zhang Lin,
Guo Baikuan,
Ma Wenjuan,
Zhang Limin,
Li Jiao,
Zhao Huijuan,
Jiang Jingying,
Gao Feng
Publication year - 2018
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.13067
Subject(s) - computer science , phase retrieval , attenuation , algorithm , regularization (linguistics) , robustness (evolution) , mathematical optimization , mathematics , artificial intelligence , optics , physics , mathematical analysis , biochemistry , chemistry , fourier transform , gene
Purpose A common problem of in‐line phase contrast imaging systems based on laboratory source and detector is the negative effects of finite source size, limited spatial resolution, and system noise. These negative effects swamp the fine phase contrast fringes and impede the precise retrieval of phase maps. This study aims to develop a novel phase retrieval method to restore phase information that is lost due to an imperfect system. Methods An improved phase‐attenuation duality ( PAD ) method based on space‐frequency joint domain iterative regularization ( JDIR ) is proposed to overcome the problems of the analytical PAD method and the spatial‐domain iterative regularization ( SDIR ) based PAD method. These problems include noise robustness and optical transfer function compensation. The proposed method was compared with the two former PAD methods through computer simulations and experiments for validation. Results Results reveal that JDIR method outperforms the other two methods in terms of improving the visibility of structures in the retrieved phase maps. Among all the phase retrieval algorithms, the TV ‐norm‐based JDIR method performed the best in considering the contrast and noise performance. Conclusions This paper provides a new method to investigate quantitative phase‐contrast imaging when considering the negative effects of an imperfect system.