Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Mary P Gronberg"'
Autor:
Kyuhak Oh, Mary P. Gronberg, Tucker J. Netherton, Bishwambhar Sengupta, Carlos E. Cardenas, Laurence E. Court, Eric C. Ford
Publikováno v:
Physics and Imaging in Radiation Oncology, Vol 26, Iss , Pp 100440- (2023)
Background and purpose: A novel cobalt-60 compensator-based intensity-modulated radiation therapy (IMRT) system was developed for a resource-limited environment but lacked an efficient dose verification algorithm. The aim of this study was to develop
Externí odkaz:
https://doaj.org/article/bb370ee59212415b88cafffb78b9c297
Autor:
Hana Baroudi, Xinru Chen, Wenhua Cao, Mohammad D. El Basha, Skylar Gay, Mary Peters Gronberg, Soleil Hernandez, Kai Huang, Zaphanlene Kaffey, Adam D. Melancon, Raymond P. Mumme, Carlos Sjogreen, January Y. Tsai, Cenji Yu, Laurence E. Court, Ramiro Pino, Yao Zhao
Publikováno v:
Journal of Imaging, Vol 9, Iss 11, p 245 (2023)
In this study, we aimed to enhance the contouring accuracy of cardiac pacemakers by improving their visualization using deep learning models to predict MV CBCT images based on kV CT or CBCT images. Ten pacemakers and four thorax phantoms were include
Externí odkaz:
https://doaj.org/article/bc25d1a54298439db150900bdb8b6edb
Autor:
Hana Baroudi, Kristy K. Brock, Wenhua Cao, Xinru Chen, Caroline Chung, Laurence E. Court, Mohammad D. El Basha, Maguy Farhat, Skylar Gay, Mary P. Gronberg, Aashish Chandra Gupta, Soleil Hernandez, Kai Huang, David A. Jaffray, Rebecca Lim, Barbara Marquez, Kelly Nealon, Tucker J. Netherton, Callistus M. Nguyen, Brandon Reber, Dong Joo Rhee, Ramon M. Salazar, Mihir D. Shanker, Carlos Sjogreen, McKell Woodland, Jinzhong Yang, Cenji Yu, Yao Zhao
Publikováno v:
Diagnostics, Vol 13, Iss 4, p 667 (2023)
Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is ‘clinical acceptability’? Quantitative and
Externí odkaz:
https://doaj.org/article/40f5b47ffd174f79a5e76c244f198726
Autor:
Mary P. Gronberg, Beth M. Beadle, Adam S. Garden, Heath Skinner, Skylar Gay, Tucker Netherton, Wenhua Cao, Carlos E. Cardenas, Christine Chung, David T. Fuentes, Clifton D. Fuller, Rebecca M. Howell, Anuja Jhingran, Tze Yee Lim, Barbara Marquez, Raymond Mumme, Adenike M. Olanrewaju, Christine B. Peterson, Ivan Vazquez, Thomas J. Whitaker, Zachary Wooten, Ming Yang, Laurence E. Court
Publikováno v:
Practical Radiation Oncology. 13:e282-e291
Purpose: This study aimed to use deep learning-based dose prediction to assess head and neck (HN) plan quality and identify suboptimal plans. Methods: A total of 245 VMAT HN plans were created using RapidPlan knowledge-based planning (KBP). A subset
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f8786d089a1a5547037613e0f03cf69
https://doi.org/10.1016/j.prro.2022.12.003
https://doi.org/10.1016/j.prro.2022.12.003
Autor:
Jay W. Burmeister, Nathan C. Busse, Ashley J. Cetnar, Rebecca R. Howell, Robert Jeraj, A. Kyle Jones, Steven H. King, Kenneth L. Matthews, Victor J. Montemayor, Wayne Newhauser, Anna E. Rodrigues, Ehsan Samei, Timothy V. Turkington, Mary P. Gronberg, Brian Loughery, Alison R. Roth, Michael C. Joiner, Edward F. Jackson, Paul A. Naine, Leonard H. Kim
Publikováno v:
Journal of applied clinical medical physics. 23(10)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae369f7212caeb1fd2f921faa9c203f0
https://pubmed.ncbi.nlm.nih.gov/36208145
https://pubmed.ncbi.nlm.nih.gov/36208145
Autor:
Mary P. Gronberg, Skylar S. Gay, Tucker J. Netherton, Dong Joo Rhee, Laurence E. Court, Carlos E. Cardenas
Publikováno v:
Medical Physics. 48:5567-5573
Purpose Radiation therapy treatment planning is a time-consuming and iterative manual process. Consequently, plan quality varies greatly between and within institutions. Artificial intelligence shows great promise in improving plan quality and reduci
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1665b5c02083a335cdce46b6c778b0e8
https://doi.org/10.1002/mp.14827
https://doi.org/10.1002/mp.14827
Autor:
Ivan Vazquez, Mary P Gronberg, Xiaodong Zhang, Laurence E Court, X Ronald Zhu, Steven J Frank, Ming Yang
Publikováno v:
Physics in Medicine & Biology. 68:095014
Objective. Robustness evaluation is critical in particle radiotherapy due to its susceptibility to uncertainties. However, the customary method for robustness evaluation only considers a few uncertainty scenarios, which are insufficient to provide a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5fffd9e77148ebb8b027021a89e30e11
https://doi.org/10.1088/1361-6560/accc08
https://doi.org/10.1088/1361-6560/accc08