no code implementations • 5 Feb 2024 • Xiao Jiang, Grace J. Gang, J. Webster Stayman
In this work, we introduce a new deep learning approach based on diffusion posterior sampling (DPS) to perform material decomposition from spectral CT measurements.
no code implementations • 3 Dec 2023 • Shudong Li, Matthew Tivnan, Yuan Shen, J. Webster Stayman
This technique is attractive since it permits a one-time, unsupervised training of a CT prior; which can then be incorporated with an arbitrary data model.
1 code implementation • 7 Feb 2023 • Jacopo Teneggi, Matthew Tivnan, J. Webster Stayman, Jeremias Sulam
Score-based generative modeling, informally referred to as diffusion models, continue to grow in popularity across several important domains and tasks.
no code implementations • 29 May 2018 • Steven Tilley II, Alejandro Sisniega, Jeffrey H. Siewerdsen, J. Webster Stayman
We show that modeling detector lag can reduce/remove the characteristic lag artifacts in head imaging in both a simulation study and physical experiments.
Medical Physics
no code implementations • 14 Dec 2017 • Steven Tilley II, Matthew Jacobson, Qian Cao, Michael Brehler, Alejandro Sisniega, Wojciech Zbijewski, J. Webster Stayman
In a simulation study, GPL-BC was able to achieve lower bias as compared to deblurring followed by FDK as well as a model-based reconstruction method without integration of measurement blur.
Medical Physics
no code implementations • 27 Jun 2017 • Steven Tilley II, Wojciech Zbijewski, J. Webster Stayman
While the high-fidelity models used here are applied using the specifications of a dedicated extremities imaging system, the methods are general and may be applied to optimize imaging performance in any CT system.
Medical Physics
no code implementations • 14 Jun 2017 • Steven Tilley II, Jeffrey H. Siewerdsen, J. Webster Stayman
In this work, we develop a forward model for flat-panel-based systems that includes blur and noise correlation associated with finite focal spot size and an indirect detector (e. g., scintillator).
Medical Physics
no code implementations • 17 Oct 2016 • Steven Tilley II, Wojciech Zbijewski, Jeffrey H. Siewerdsen, J. Webster Stayman
In both experiments image quality using the shift-variant model was significantly improved over approaches that modeled no blur or only a shift-invariant blur, suggesting a potential means to overcome traditional CBCT spatial resolution and system design limitations.
Medical Physics Optimization and Control