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Refik Mert Cam

Showing results (1-10 of 8) with videos related to

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Inverse Problems|June 27, 2024
Learning a stable approximation of an existing but unknown inverse mapping: application to the half-time circular Radon transformRefik Mert Cam, Umberto Villa, Mark A Anastasio
Photoacoustics|February 2, 2026
Application of a virtual imaging framework for investigating a deep learning-based reconstruction method for 3D quantitative photoacoustic computed tomographyRefik Mert Cam, Seonyeong Park, Umberto Villa, et al.
IEEE Transactions on Computational Imaging|July 29, 2025
ProxNF: Neural Field Proximal Training for High-Resolution 4D Dynamic Image ReconstructionLuke Lozenski, Refik Mert Cam, Mark D Pagel, et al.
Arxiv|February 6, 2026
Benchmarking Deep Learning-Based Reconstruction Methods for Photoacoustic Computed Tomography with Clinically Relevant Synthetic DatasetsPanpan Chen, Seonyeong Park, Gangwon Jeong, et al.
Journal of Biomedical Optics|January 22, 2024
Spatiotemporal image reconstruction to enable high-frame-rate dynamic photoacoustic tomography with rotating-gantry volumetric imagersRefik Mert Cam, Chao Wang, Weylan Thompson, et al.
Journal of Biomedical Optics|June 22, 2023
Stochastic three-dimensional numerical phantoms to enable computational studies in quantitative optoacoustic computed tomography of breast cancerSeonyeong Park, Umberto Villa, Fu Li, et al.
IEEE Transactions on Medical Imaging|July 22, 2025
Learning a Filtered Backprojection Reconstruction Method for Photoacoustic Computed Tomography with Hemispherical Measurement GeometriesPanpan Chen, Seonyeong Park, Refik Mert Cam, et al.
Arxiv|December 16, 2024
Learning a Filtered Backprojection Reconstruction Method for Photoacoustic Computed Tomography with Hemispherical Measurement GeometriesPanpan Chen, Seonyeong Park, Refik Mert Cam, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Inverse Problems|June 27, 2024
Learning a stable approximation of an existing but unknown inverse mapping: application to the half-time circular Radon transformRefik Mert Cam, Umberto Villa, Mark A Anastasio
Photoacoustics|February 2, 2026
Application of a virtual imaging framework for investigating a deep learning-based reconstruction method for 3D quantitative photoacoustic computed tomographyRefik Mert Cam, Seonyeong Park, Umberto Villa, et al.
IEEE Transactions on Computational Imaging|July 29, 2025
ProxNF: Neural Field Proximal Training for High-Resolution 4D Dynamic Image ReconstructionLuke Lozenski, Refik Mert Cam, Mark D Pagel, et al.
Arxiv|February 6, 2026
Benchmarking Deep Learning-Based Reconstruction Methods for Photoacoustic Computed Tomography with Clinically Relevant Synthetic DatasetsPanpan Chen, Seonyeong Park, Gangwon Jeong, et al.
Journal of Biomedical Optics|January 22, 2024
Spatiotemporal image reconstruction to enable high-frame-rate dynamic photoacoustic tomography with rotating-gantry volumetric imagersRefik Mert Cam, Chao Wang, Weylan Thompson, et al.
Journal of Biomedical Optics|June 22, 2023
Stochastic three-dimensional numerical phantoms to enable computational studies in quantitative optoacoustic computed tomography of breast cancerSeonyeong Park, Umberto Villa, Fu Li, et al.
IEEE Transactions on Medical Imaging|July 22, 2025
Learning a Filtered Backprojection Reconstruction Method for Photoacoustic Computed Tomography with Hemispherical Measurement GeometriesPanpan Chen, Seonyeong Park, Refik Mert Cam, et al.
Arxiv|December 16, 2024
Learning a Filtered Backprojection Reconstruction Method for Photoacoustic Computed Tomography with Hemispherical Measurement GeometriesPanpan Chen, Seonyeong Park, Refik Mert Cam, et al.
Pageof 1