PMS-GAN: Parallel Multi-Stream Generative Adversarial Network for Multi-Material Decomposition in Spectral Computed Tomography

Geng M, Tian Z, Jiang Z, You Y, Feng X, Xia Y, Yang K, Ren Q, Meng X, Maier A, Lu Y (2021)

Publication Type: Journal article

Publication year: 2021

Journal

IEEE Transactions on Medical Imaging Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 40

Pages Range: 571-584

Journal Issue: 2

DOI: 10.1109/TMI.2020.3031617

Abstract

Spectral computed tomography is able to provide quantitative information on the scanned object and enables material decomposition. Traditional projection-based material decomposition methods suffer from the nonlinearity of the imaging system, which limits the decomposition accuracy. Inspired by the generative adversarial network, we proposed a novel parallel multi-stream generative adversarial network (PMS-GAN) to perform projection-based multi-material decomposition in spectral computed tomography. By designing the differential map and incorporating the adversarial network into loss function, the decomposition accuracy was significantly improved with robust performance. The proposed network was quantitatively evaluated by both simulation and experimental study. The results show that PMS-GAN outperformed the reference methods with certain robustness. Compared with Pix2pix-GAN, PMS-GAN increased the structural similarity index by 172% on the contrast agent Ultravist370, 11% on bones, and 71% on bone marrow, respectively, in a simulated test scenario. In an experimental test scenario, 9% and 38% improvements of the structural similarity index on the biopsy needle and on a torso phantom were observed, respectively. The proposed network demonstrates its capability of multi-material decomposition and has certain potential toward clinical applications.

Authors with CRIS profile

Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

Additional Organisation(s)

Lehrstuhl für Informatik 5 (Mustererkennung)

Involved external institutions

Peking University (PKU) / 北京大学 CN China (CN) Hebei University / 河北大学 CN China (CN) University of Leeds GB United Kingdom (GB)

How to cite

APA:

Geng, M., Tian, Z., Jiang, Z., You, Y., Feng, X., Xia, Y.,... Lu, Y. (2021). PMS-GAN: Parallel Multi-Stream Generative Adversarial Network for Multi-Material Decomposition in Spectral Computed Tomography. IEEE Transactions on Medical Imaging, 40(2), 571-584. https://doi.org/10.1109/TMI.2020.3031617

MLA:

Geng, Mufeng, et al. "PMS-GAN: Parallel Multi-Stream Generative Adversarial Network for Multi-Material Decomposition in Spectral Computed Tomography." IEEE Transactions on Medical Imaging 40.2 (2021): 571-584.

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