Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Randall K. Ten Haken, PhD"'
Autor:
Daniel R. Owen, PhD, Yilun Sun, PhD, Jim C. Irrer, BS, Matthew J. Schipper, PhD, Caitlin A. Schonewolf, MD, Stefanie Galbán, PhD, Shruti Jolly, MD, Randall K. Ten Haken, PhD, C.J. Galbán, PhD, M.M. Matuszak, PhD
Publikováno v:
Advances in Radiation Oncology, Vol 7, Iss 4, Pp 100980- (2022)
Purpose: Parametric response mapping (PRM) of high-resolution, paired inspiration and expiration computed tomography (CT) scans is a promising analytical imaging technique that is currently used in diagnostic applications and offers the ability to ch
Externí odkaz:
https://doaj.org/article/493ca44e5fb047b1ae23c231d5b19fd9
Autor:
Daniel R. Owen, BS, Yilun Sun, PhD, Philip S. Boonstra, PhD, Matthew McFarlane, MD, PhD, Benjamin L. Viglianti, MD, PhD, James M. Balter, PhD, Issam El Naqa, PhD, Matthew J. Schipper, PhD, Caitlin A. Schonewolf, MD, Randall K. Ten Haken, PhD, Feng-Ming S. Kong, MD, PhD, Shruti Jolly, MD, Martha M. Matuszak, PhD
Publikováno v:
Advances in Radiation Oncology, Vol 6, Iss 3, Pp 100666- (2021)
Purpose: Dose to normal lung has commonly been linked with radiation-induced lung toxicity (RILT) risk, but incorporating functional lung metrics in treatment planning may help further optimize dose delivery and reduce RILT incidence. The purpose of
Externí odkaz:
https://doaj.org/article/ffa15dd215cd46049851708624b250a3
Priority-driven plan optimization in locally advanced lung patients based on perfusion SPECT imaging
Autor:
Martha M. Matuszak, PhD, Charles Matrosic, MS, David Jarema, Daniel L. McShan, Matthew H. Stenmark, MD, Dawn Owen, MD, Shruti Jolly, MD, Feng-Ming (Spring) Kong, MD, Randall K. Ten Haken, PhD
Publikováno v:
Advances in Radiation Oncology, Vol 1, Iss 4, Pp 281-289 (2016)
Purpose: Limits on mean lung dose (MLD) allow for individualization of radiation doses at safe levels for patients with lung tumors. However, MLD does not account for individual differences in the extent or spatial distribution of pulmonary dysfuncti
Externí odkaz:
https://doaj.org/article/975d856a76364004a9e5bd42e5377d23
Autor:
Charles S. Mayo, PhD, Marc L. Kessler, PhD, Avraham Eisbruch, MD, Grant Weyburne, BS, Mary Feng, MD, James A. Hayman, MD, Shruti Jolly, MD, Issam El Naqa, PhD, Jean M. Moran, PhD, Martha M. Matuszak, PhD, Carlos J. Anderson, PhD, Lynn P. Holevinski, BS, Daniel L. McShan, PhD, Sue M. Merkel, MSA RT(R)(T), Sherry L. Machnak, MBA RT(T), Theodore S. Lawrence, MD PhD, Randall K. Ten Haken, PhD
Publikováno v:
Advances in Radiation Oncology, Vol 1, Iss 4, Pp 260-271 (2016)
Although large volumes of information are entered into our electronic health care records, radiation oncology information systems and treatment planning systems on a daily basis, the goal of extracting and using this big data has been slow to emerge.
Externí odkaz:
https://doaj.org/article/8c1c148fd26c41019b2e9725732bed0a