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pro vyhledávání: '"Maltz, A"'
Autor:
Maltz, Maxwell G. A., Thomas, Peter A., Lovell, Christoper C., Roper, William J., Vijayan, Aswin P., Irodotou, Dimitrios, Liao, Shihong, Seeyave, Louise T. C., Wilkins, Stephen M.
Understanding the galaxy-halo relationship is not only key for elucidating the interplay between baryonic and dark matter, it is essential for creating large mock galaxy catalogues from N-body simulations. High-resolution hydrodynamical simulations a
Externí odkaz:
http://arxiv.org/abs/2410.24082
This study aims to improve photon counting CT (PCCT) image resolution using denoising diffusion probabilistic models (DDPM). Although DDPMs have shown superior performance when applied to various computer vision tasks, their effectiveness has yet to
Externí odkaz:
http://arxiv.org/abs/2408.15283
Autor:
Han, Shuo, Xu, Yongshun, Wang, Dayang, Morovati, Bahareh, Zhou, Li, Maltz, Jonathan S., Wang, Ge, Yu, Hengyong
Cardiac computed tomography (CT) has emerged as a major imaging modality for the diagnosis and monitoring of cardiovascular diseases. High temporal resolution is essential to ensure diagnostic accuracy. Limited-angle data acquisition can reduce scan
Externí odkaz:
http://arxiv.org/abs/2405.14770
Photon-counting CT using a Conditional Diffusion Model for Super-resolution and Texture-preservation
Ultra-high resolution images are desirable in photon counting CT (PCCT), but resolution is physically limited by interactions such as charge sharing. Deep learning is a possible method for super-resolution (SR), but sourcing paired training data that
Externí odkaz:
http://arxiv.org/abs/2402.16212
MACE CT Reconstruction for Modular Material Decomposition from Energy Resolving Photon-Counting Data
Autor:
Jadue, Natalie M., Nagare, Madhuri, Maltz, Jonathan S., Buzzard, Gregery T., Bouman, Charles A.
X-ray computed tomography (CT) based on photon counting detectors (PCD) extends standard CT by counting detected photons in multiple energy bins. PCD data can be used to increase the contrast-to-noise ratio (CNR), increase spatial resolution, reduce
Externí odkaz:
http://arxiv.org/abs/2402.00967
Autor:
Hein, Dennis, Holmin, Staffan, Szczykutowicz, Timothy, Maltz, Jonathan S, Danielsson, Mats, Wang, Ge, Persson, Mats
Diffusion and Poisson flow models have shown impressive performance in a wide range of generative tasks, including low-dose CT image denoising. However, one limitation in general, and for clinical applications in particular, is slow sampling. Due to
Externí odkaz:
http://arxiv.org/abs/2312.09754
Autor:
Hein, Dennis, Holmin, Staffan, Szczykutowicz, Timothy, Maltz, Jonathan S, Danielsson, Mats, Wang, Ge, Persson, Mats
Deep learning has proven to be important for CT image denoising. However, such models are usually trained under supervision, requiring paired data that may be difficult to obtain in practice. Diffusion models offer unsupervised means of solving a wid
Externí odkaz:
http://arxiv.org/abs/2309.01553
Autor:
Dennis Hein, Staffan Holmin, Timothy Szczykutowicz, Jonathan S. Maltz, Mats Danielsson, Ge Wang, Mats Persson
Publikováno v:
Visual Computing for Industry, Biomedicine, and Art, Vol 7, Iss 1, Pp 1-14 (2024)
Abstract Deep learning (DL) has proven to be important for computed tomography (CT) image denoising. However, such models are usually trained under supervision, requiring paired data that may be difficult to obtain in practice. Diffusion models offer
Externí odkaz:
https://doaj.org/article/cf9f018fc24247cb8dcd2c4abe419cda
Autor:
Thomas, Peter A., Lovell, Christopher C., Maltz, Maxwell G. A., Vijayan, Aswin P., Wilkins, Stephen M., Irodotou, Dimitrios, Roper, William J., Seeyave, Louise
Upcoming deep galaxy surveys with JWST will probe galaxy evolution during the epoch of reionisation (EoR, $5\leq z\leq10$) over relatively compact areas (e.g. $\sim$ 300\,arcmin$^2$ for the JADES GTO survey). It is therefore imperative that we unders
Externí odkaz:
http://arxiv.org/abs/2301.09510
Autor:
Mia Rose Maltz, Michael F. Allen, Michala L. Phillips, Rebecca R. Hernandez, Hannah B. Shulman, Linton Freund, Lela V. Andrews, Jon K. Botthoff, Emma L. Aronson
Publikováno v:
Frontiers in Microbiomes, Vol 3 (2024)
IntroductionThe 1980 eruption of Mount St. Helens had devastating effects above and belowground in forested montane ecosystems, including the burial and destruction of soil microbes. Soil microbial propagules and legacies in recovering ecosystems are
Externí odkaz:
https://doaj.org/article/16c007a6135a4ebb96b6c7c9b78e55c1