Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Dennis S. Mackin"'
Autor:
Jerimy C. Polf, Carlos A. Barajas, Stephen W. Peterson, Dennis S. Mackin, Sam Beddar, Lei Ren, Matthias K. Gobbert
Publikováno v:
Frontiers in Physics, Vol 10 (2022)
We studied the application of a deep, fully connected Neural Network (NN) to process prompt gamma (PG) data measured by a Compton camera (CC) during the delivery of clinical proton radiotherapy beams. The network identifies 1) recorded “bad” PG e
Externí odkaz:
https://doaj.org/article/9cd9eb047187490090e5ea09945565bf
Autor:
Souptik Barua, Hesham Elhalawani, Stefania Volpe, Karine A. Al Feghali, Pei Yang, Sweet Ping Ng, Baher Elgohari, Robin C. Granberry, Dennis S. Mackin, G. Brandon Gunn, Katherine A. Hutcheson, Mark S. Chambers, Laurence E. Court, Abdallah S. R. Mohamed, Clifton D. Fuller, Stephen Y. Lai, Arvind Rao
Publikováno v:
Frontiers in Artificial Intelligence, Vol 4 (2021)
Osteoradionecrosis (ORN) is a major side-effect of radiation therapy in oropharyngeal cancer (OPC) patients. In this study, we demonstrate that early prediction of ORN is possible by analyzing the temporal evolution of mandibular subvolumes receiving
Externí odkaz:
https://doaj.org/article/5ff9cfb7d789476c85ba592f8d0e0641
Autor:
Hesham Elhalawani, Timothy A. Lin, Stefania Volpe, Abdallah S. R. Mohamed, Aubrey L. White, James Zafereo, Andrew J. Wong, Joel E. Berends, Shady AboHashem, Bowman Williams, Jeremy M. Aymard, Aasheesh Kanwar, Subha Perni, Crosby D. Rock, Luke Cooksey, Shauna Campbell, Pei Yang, Khahn Nguyen, Rachel B. Ger, Carlos E. Cardenas, Xenia J. Fave, Carlo Sansone, Gabriele Piantadosi, Stefano Marrone, Rongjie Liu, Chao Huang, Kaixian Yu, Tengfei Li, Yang Yu, Youyi Zhang, Hongtu Zhu, Jeffrey S. Morris, Veerabhadran Baladandayuthapani, John W. Shumway, Alakonanda Ghosh, Andrei Pöhlmann, Hady A. Phoulady, Vibhas Goyal, Guadalupe Canahuate, G. Elisabeta Marai, David Vock, Stephen Y. Lai, Dennis S. Mackin, Laurence E. Court, John Freymann, Keyvan Farahani, Jayashree Kaplathy-Cramer, Clifton D. Fuller
Publikováno v:
Frontiers in Oncology, Vol 8 (2018)
Radiomics leverages existing image datasets to provide non-visible data extraction via image post-processing, with the aim of identifying prognostic, and predictive imaging features at a sub-region of interest level. However, the application of radio
Externí odkaz:
https://doaj.org/article/0470a3fe0ec44bbd97b0008f84f49829
Autor:
Constance A Owens, Christine B Peterson, Chad Tang, Eugene J Koay, Wen Yu, Dennis S Mackin, Jing Li, Mohammad R Salehpour, David T Fuentes, Laurence E Court, Jinzhong Yang
Publikováno v:
PLoS ONE, Vol 13, Iss 10, p e0205003 (2018)
PURPOSE:To evaluate the uncertainty of radiomics features from contrast-enhanced breath-hold helical CT scans of non-small cell lung cancer for both manual and semi-automatic segmentation due to intra-observer, inter-observer, and inter-software reli
Externí odkaz:
https://doaj.org/article/89be9329dde9478c872bb730160799c2
Publikováno v:
IEEE Transactions on Radiation and Plasma Medical Sciences. 5:383-391
The purpose of this study was to determine the types, proportions, and energies of secondary particle interactions in a Compton camera (CC) during the delivery of clinical proton beams. The delivery of clinical proton pencil beams ranging from 70 to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5823b9dba617dd978d99699fc4675f67
https://doi.org/10.1109/trpms.2020.3030166
https://doi.org/10.1109/trpms.2020.3030166
Autor:
Hannah J. Lee, David S Followill, Laurence E. Court, Yao Ding, Jihong Wang, Angela Steinmann, Rachel B. Ger, Joonsang Lee, Dennis S. Mackin, Jinzhong Yang, Constance A. Owens
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
Scientific Reports
Scientific Reports
Radiomics involves high-throughput extraction of large numbers of quantitative features from medical images and analysis of these features to predict patients’ outcome and support clinical decision-making. However, radiomics features are sensitive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6dae059237f7dd332508abe4d19af4ba
https://doaj.org/article/54192feb84fc48fc863463a32b264999
https://doaj.org/article/54192feb84fc48fc863463a32b264999
Autor:
Stephen Y. Lai, Clifton D. Fuller, Mark S. Chambers, Pei Yang, Sweet Ping Ng, Laurence E. Court, G. Brandon Gunn, Arvind Rao, R. Granberry, Hesham Elhalawani, Karine A. Al Feghali, Dennis S. Mackin, Abdallah S.R. Mohamed, Souptik Barua, Stefania Volpe, Baher Elgohari, Katherine A. Hutcheson
Osteoradionecrosis (ORN) is a major side-effect of radiation therapy in oropharyngeal cancer (OPC) patients. In this study, we demonstrate that early prediction of ORN is possible by analyzing the temporal evolution of mandibular subvolumes receiving
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0fce62d7ce60eeb6086ae1ee597d7433
https://doi.org/10.1101/2020.10.09.20208827
https://doi.org/10.1101/2020.10.09.20208827
Autor:
R. Jason Stafford, Shouhao Zhou, Daniel F. Craft, Hesham Elhalawani, Dennis S. Mackin, Clifton D. Fuller, Laurence E. Court, A. Kyle Jones, Rachel B. Ger, Heng Li, Rebecca M. Howell, Rick R. Layman
Publikováno v:
Computerized Medical Imaging and Graphics. 69:134-139
Radiomics studies have demonstrated the potential use of quantitative image features to improve prognostic stratification of patients with head and neck cancer. Imaging protocol parameters that can affect radiomics feature values have been investigat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e3fcda7e2e28d10261dfa2e9e3d6c66
https://doi.org/10.1016/j.compmedimag.2018.09.002
https://doi.org/10.1016/j.compmedimag.2018.09.002
Autor:
Jinzhong Yang, Dennis S. Mackin, A. Kyle Jones, Laurence E. Court, Steve Bache, Cristina Dodge, X Fave, Lifei Zhang, Rachel B. Ger, Charles Dodge, Pai Chun Chi
Publikováno v:
Scientific Reports, Vol 8, Iss 1, Pp 1-10 (2018)
Scientific Reports
Scientific Reports
Variability in the x-ray tube current used in computed tomography may affect quantitative features extracted from the images. To investigate these effects, we scanned the Credence Cartridge Radiomics phantom 12 times, varying the tube current from 25
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82175cc821d07fb3d0a3611185bfbbd5
http://link.springer.com/article/10.1038/s41598-018-20713-6
http://link.springer.com/article/10.1038/s41598-018-20713-6
Autor:
Laurence E. Court, Abdallah S.R. Mohamed, Yuan Ji, Mona Kamal, Yitan Zhu, Andrew J. Wong, Aasheesh Kanwar, Stephen Y. Lai, Shengjie Yang, Clifton D. Fuller, Dennis S. Mackin, Hesham Elhalawani, Yao Ding, Heath D. Skinner, J.A. Messer, Jay C. Shiao, Subhajit Sengupta, Lifei Zhang, Lin Wei
Publikováno v:
JCO clinical cancer informatics. 3
Purpose Recent data suggest that imaging radiomic features of a tumor could be indicative of important genomic biomarkers. Understanding the relationship between radiomic and genomic features is important for basic cancer research and future patient
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::189ca3fff6f7c3320bff0fd797479160
https://pubmed.ncbi.nlm.nih.gov/30730765
https://pubmed.ncbi.nlm.nih.gov/30730765