One-Step Method for Material Quantitation Using In-Line Tomography With Single Scanning

• Published in: IEEE transactions on biomedical engineering Vol. 70; no. 1; pp. 15 - 26
• Main Authors: Liao, Suyu, Deng, Shiwo, Zhu, Yining, Zhang, Huitao, Zhu, Peiping, Zhang, Kai, Zhao, Xing
• Format: Journal Article
• Language: English
• Published: United States IEEE 01-01-2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Absorption; Algorithms; Atomic properties; Biomedical materials; Computed tomography; Decomposition; Fresnel diffraction; Gratings; Image Processing, Computer-Assisted - methods; Image quality; Image reconstruction; Imaging; Iterative methods; linear approximation; material quantitation; Noise reduction; one-step method; Phantoms, Imaging; Phase retrieval; phase-contrast; Quantitation; Quantitative analysis; Refractivity; Scanning; Signal to noise ratio; single scanning; Tomography; Tomography, X-Ray Computed - methods; X-ray imaging
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2022.3181153

Objective: Quantitative technique based on In-line phase-contrast computed tomography with single scanning attracts more attention in application due to the flexibility of the implementation. However, the quantitative results usually suffer from artifacts and noise since the phase retrieval and reconstruction are independent ("two-step") without feedback from the original data. The work aims to investigate a method for material quantitation to improve the image quality of In-line tomography within single scanning. Method: An iterative method based Fresnel diffraction imaging model is developed in this work, which directly reconstructs the refractive index decrement <inline-formula><tex-math notation="LaTeX">\delta</tex-math></inline-formula> and imaginary <inline-formula><tex-math notation="LaTeX">\beta</tex-math></inline-formula> of the object from observed data ("one-step"). Moreover, high-quality material decomposition results are obtained by using a linear approximation in the iterative process. Results: Compared with the existing methods, Our method shows a higher peak signal-to-noise ratio and structural similarity in numerical experimental results. Additionally, the quantitation accuracy of the proposed method is greater than 97.2<inline-formula><tex-math notation="LaTeX">\%</tex-math></inline-formula> by calculating the equivalent atomic number of the decomposed basic material in the real experiment. Conclusion: We demonstrate that this one-step method greatly reduces noise and improves quantitative reconstruction and decomposition results. Significance: This algorithm has the potential for quantitative imaging research using In-line tomography in future biomedical applications.