Mr. Xiao Jiang Profile

Xiao Jiang

at Johns Hopkins Univ

SPIE Involvement:

Author

Publications (9)

SPIE Journal Paper | 30 August 2024

CT reconstruction using diffusion posterior sampling conditioned on a nonlinear measurement model

Shudong Li, Xiao Jiang, Matthew Tivnan, Grace J. Gang, Yuan Shen, J. Webster Stayman

JMI, Vol. 11, Issue 04, 043504, (August 2024) https://doi.org/10.1117/12.10.1117/1.JMI.11.4.043504

KEYWORDS: Double positive medium, Diffusion, CT reconstruction, Education and training, Data modeling, Systems modeling, Reverse modeling, Lung, Computed tomography, Error analysis

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Proceedings Article | 1 April 2024 Paper

Robustness of spectral digital subtraction angiography to patient motion

Suyu Liao, Xiao Jiang, Xiaoxuan Zhang, Grace Gang

Proceedings Volume 12925, 1292544 (2024) https://doi.org/10.1117/12.3008255

KEYWORDS: Image registration, Image processing, Angiography

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Spectral imaging is an active area of investigation for interventional applications. We have previously proposed a joint processing strategy that leverage both temporal and spectral information to obtain digital subtraction angiograms (DSA). This strategy allows for the isolation of iodine signal using measurements from just two energy channels and can yield a noise advantage compared to alternative spectral acquisitions. Previous investigations imposed fairly restrictive assumptions on patient motion (at least one material map is stationary pre- and post-contrast). In this work, we investigate the performance of the joint processing strategy without such assumptions. Specifically, we included a simple affine registration prior to material decomposition to mitigate gross patient motion. Assuming such registration can compensate motion in one tissue type (e.g., bone which exhibits locally rigid motion), we then use the total of four energy measurements to solve for four unknowns: water pre- and post-contrast, calcium, and iodine. This method accommodates registration mismatches in the pre- and post-contrast water images. To evaluate this method, we simulated a head phantom with a backward tilt about the lateral axis between the pre- and post-contrast acquisitions, as well as an abdomen phantom with cardiac, breathing, and a vertical translation. Results from the joint processing strategy was compared with that using temporal subtraction. Following four-material decomposition, both water images and calcium image show a small bias around 5% from ground truth. The iodine image contains bias primarily concentrated around bone edges. Compared to temporal subtraction, motion artifact from soft tissue is largely eliminated while that from bone is reduced in magnitude. As a result, improvement in motion artifact and iodine visibility is improved across the image. The improvement is especially obvious in the abdomen where soft tissue motion is dominant. We demonstrated in this work that the joint processing strategy is robust against motion artifact in the presence of gross patient motion and can present advantages compared to temporal subtraction, providing further support for the clinical translations of spectral DSA.

Proceedings Article | 1 April 2024 Presentation + Paper

Design optimization of a triple-layer flat-panel detector for three-material decomposition

Xiao Jiang, Matthew Tivnan, Xiaoxuan Zhang, J. Webster Stayman, Grace Gang

Proceedings Volume 12925, 129250U (2024) https://doi.org/10.1117/12.3006385

KEYWORDS: Design, Imaging systems, X-rays, Model based design, Radiography, Fluoroscopy, X ray detectors

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Proceedings Article | 7 April 2023 Presentation + Paper

Approaches for three material decomposition using a triple-layer flat-panel detector

Xiao Jiang, J. Webster Stayman, Grace Gang

Proceedings Volume 12463, 124630X (2023) https://doi.org/10.1117/12.2654468

KEYWORDS: Iodine, Calcium, Radiography, Model-based design, Modulation transfer functions, Deep learning, X-rays, Visualization, Network architectures, Modal decomposition

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Proceedings Article | 18 October 2022 Open Access

Residual W-shape network (ResWnet) for dual-energy cone-beam CT imaging

Xiao Jiang, Hehe Cui, Zihao Liu, Lei Zhu

Proceedings Volume 12304, 1230427 (2022) https://doi.org/10.1117/12.2646505

KEYWORDS: Bone, Computed tomography, Tissues, Performance modeling, X-ray computed tomography, Dual energy imaging, Denoising, Interference (communication), Signal attenuation, Data modeling

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Proceedings Article | 4 April 2022 Poster + Presentation + Paper

A novel female pelvis phantom for evaluation of imaging and dose calculation in CBCT-based cervical brachytherapy

Ailin Wu, Xiao Jiang, Hehe Cui, Xue Ke, Aidong Wu, Lei Zhu

Proceedings Volume 12031, 120313V (2022) https://doi.org/10.1117/12.2605531

KEYWORDS: Computed tomography, 3D modeling, Image quality, Cervical cancer, Exact cone beam reconstruction

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Proceedings Article | 16 March 2020 Paper

Accelerated reconstruction for inverse geometry CT via derivative back-projection filtration

Xiao Jiang, Bangyan Huang, Lei Zhu

Proceedings Volume 11312, 113123K (2020) https://doi.org/10.1117/12.2548840

KEYWORDS: Reconstruction algorithms, Spatial resolution, Algorithm development, Computer simulations, Convolution, X-ray sources

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Proceedings Article | 16 March 2020 Paper

A prototype system of upright dedicated cone-beam breast CT

Gongming Xu, Chengyijue Fang, Xiao Jiang, Lei Zhu

Proceedings Volume 11312, 1131256 (2020) https://doi.org/10.1117/12.2541709

KEYWORDS: Breast, Prototyping, Mammography, Sensors, Imaging systems, Chest, Spatial resolution, X-rays, X-ray sources, Ultrasonography

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Proceedings Article | 1 March 2019 Paper

A direct filtered back-projection reconstruction method for inverse geometry CT without gridding: a simulation study

Xiao Jiang, Lei Zhu

Proceedings Volume 10948, 1094858 (2019) https://doi.org/10.1117/12.2507356

KEYWORDS: Reconstruction algorithms, Spatial resolution, Modulation transfer functions, X-ray sources, Data acquisition, Detection and tracking algorithms, Algorithm development, Computer simulations, X-ray computed tomography

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Showing 5 of 9 publications

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