Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Gregery T. Buzzard"'
Autor:
Shimin Tang, Singanallur V. Venkatakrishnan, Mohammad S. N. Chowdhury, Diyu Yang, Megan Gober, George J. Nelson, Maria Cekanova, Alexandru S. Biris, Gregery T. Buzzard, Charles A. Bouman, Harley D. Skorpenske, Hassina Z. Bilheux
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract We present the first machine learning-based autonomous hyperspectral neutron computed tomography experiment performed at the Spallation Neutron Source. Hyperspectral neutron computed tomography allows the characterization of samples by enabl
Externí odkaz:
https://doaj.org/article/98013f6bc0d9419ba7069c14a41937de
Publikováno v:
IEEE Signal Processing Magazine. 40:85-97
Publikováno v:
IEEE Transactions on Computational Imaging. 8:81-95
Applications in materials and biological imaging are limited by the ability to collect high-resolution data over large areas in practical amounts of time. One solution to this problem is to collect low-resolution data and interpolate to produce a hig
CT imaging works by reconstructing an object of interest from a collection of projections. Traditional methods such as filtered-back projection (FBP) work on projection images acquired around a fixed rotation axis. However, for some CT problems, it i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc61b6c4b0b4686cf04b3a56fc183a4c
http://arxiv.org/abs/2209.07561
http://arxiv.org/abs/2209.07561
Coherent plug-and-play artifact removal: Physics-based deep learning for imaging through aberrations
Autor:
Casey J. Pellizzari, Timothy J. Bate, Kevin P. Donnelly, Gregery T. Buzzard, Charles A. Bouman, Mark F. Spencer
Publikováno v:
Optics and Lasers in Engineering. 164:107496
Publikováno v:
IEEE Transactions on Control Systems Technology. 28:1092-1099
Embedded systems require control algorithms that are safe and able to operate in embedded platforms with extreme limitations on energy, memory, and area footprint. Nonlinear model predictive control (NMPC) algorithms respect operational constraints t
Autor:
Edward T. Reehorst, Charles A. Bouman, Sizhou Liu, Philip Schniter, Gregery T. Buzzard, Rizwan Ahmad, Stanley H. Chan
Publikováno v:
IEEE Signal Process Mag
Magnetic Resonance Imaging (MRI) is a non-invasive diagnostic tool that provides excellent soft-tissue contrast without the use of ionizing radiation. Compared to other clinical imaging modalities (e.g., CT or ultrasound), however, the data acquisiti
Publikováno v:
PLoS Computational Biology, Vol 11, Iss 9, p e1004488 (2015)
This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under
Externí odkaz:
https://doaj.org/article/f37c2bd883b74af092130b3677abaacc
Publikováno v:
PLoS Computational Biology, Vol 10, Iss 4, p e1003546 (2014)
Computational approaches to tune the activation of intracellular signal transduction pathways both predictably and selectively will enable researchers to explore and interrogate cell biology with unprecedented precision. Techniques to control complex
Externí odkaz:
https://doaj.org/article/ad9bf01d162e485fb5f266261066d568
Publikováno v:
PLoS Computational Biology, Vol 10, Iss 3, p e1003498 (2014)
Discovery in developmental biology is often driven by intuition that relies on the integration of multiple types of data such as fluorescent images, phenotypes, and the outcomes of biochemical assays. Mathematical modeling helps elucidate the biologi
Externí odkaz:
https://doaj.org/article/31ac7eb35617470dafa944717bd837b4