Abstract
The phase retrieval is an important task in x-ray phase contrast imaging. The robustness of phase retrieval is especially important for potential medical imaging applications such as phase contrast mammography. Recently the authors developed an iterative phase retrieval algorithm, the attenuation-partition based algorithm, for the phase retrieval in inline phase-contrast imaging [1]. Applied to experimental images, the algorithm was proven to be fast and robust. However, a quantitative analysis of the performance of this new algorithm is desirable. In this work, we systematically compared the performance of this algorithm with other two widely used phase retrieval algorithms, namely the Gerchberg-Saxton (GS) algorithm and the Transport of Intensity Equation (TIE) algorithm. The systematical comparison is conducted by analyzing phase retrieval performances with a digital breast specimen model. We show that the proposed algorithm converges faster than the GS algorithm in the Fresnel diffraction regime, and is more robust against image noise than the TIE algorithm. These results suggest the significance of the proposed algorithm for future medical applications with the x-ray phase contrast imaging technique.
Highlights
Differing from the conventional x-ray imaging, which relies on the small differences in xray attenuation changes between tissues variable structure, inline phase contrast imaging is based on the tissues’ phase-shifts diffraction from the object to the detector
We assumed that the x-ray source is a quasi-monochromatic point source
With the Wigner function based phase space formalism, we have proved that the coherence degree of a finite-size focal spot can be accounted for by the optical transfer function OTFG.U.(u⃗/M) for the geometrical unsharpness associated with the finite-size source [20]: where Ispot(ξ⃗) is the intensity distribution of the focal spot
Summary
Differing from the conventional x-ray imaging, which relies on the small differences in xray attenuation changes between tissues variable structure, inline phase contrast imaging is based on the tissues’ phase-shifts diffraction from the object to the detector. In [1], the authors developed an Attenuation-Partition Based Algorithm (APBA) based on the phase-attenuation duality property of soft tissues under higher x-ray energy. This algorithm is fast and stable for potential medical imaging. We compared the performance of this algorithm with the TIE algorithm for two groups of data under the condition of medical imaging in [1], including the phase retrieval from phase-contrast images of a breast lumpectomy specimen. We give a measure, called total variation, used to evaluate the closeness of two image data This measure is used as a quantitative standard in comparing the performance between different algorithms . The attenuation-partition based algorithm (APBA) and an image accuracy measure
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