| LDR | | 02748nam u200445 4500 |
| 001 | | 000000419954 |
| 005 | | 20190215164105 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438354586 |
| 035 | |
▼a (MiAaPQ)AAI10933828 |
| 035 | |
▼a (MiAaPQ)wisc:15741 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 616 |
| 100 | 1 |
▼a Patton, Taylor J. |
| 245 | 10 |
▼a Quantifying and Modeling Radiation Therapy-induced Ventilation Changes and Investigating the Robustness of 4DCT-based Functional Avoidance. |
| 260 | |
▼a [S.l.]:
▼b The University of Wisconsin - Madison.,
▼c 2018. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
| 300 | |
▼a 151 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B. |
| 500 | |
▼a Adviser: John E. Bayouth. |
| 502 | 1 |
▼a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2018. |
| 520 | |
▼a Four-dimensional computed tomography-based ventilation is a developing method for estimating the lung function of patients. The response of 4DCT-based ventilation to radiation therapy (RT) has remained largely uncharacterized. The purpose of thi |
| 520 | |
▼a Pre-RT and post-RT ventilation estimations were acquired, and the voxel-wise response of the post-RT ventilation to dose and pre-RT ventilation was determined. High-dose regions sustained more ventilation decline than low-dose regions. Increased |
| 520 | |
▼a A polynomial regression model was created using pre-RT ventilation and dose to predict post-RT ventilation. This model showed significant predictive power on the cross-validation dataset as measured by gamma pass rates. The model was applied to |
| 520 | |
▼a Predictive models were created to include the average heart dose and average lobe dose using linear regression and regression neural networks. The linear regression model including heart and lobe dose had the highest predictive power as measured |
| 520 | |
▼a The impact of respiratory motion on functional avoidance was investigated using three representative dose distributions. The worst-case scenario dose distribution represented the patient at end-inspiration for the entirety of treatment. However, |
| 590 | |
▼a School code: 0262. |
| 650 | 4 |
▼a Medical imaging. |
| 650 | 4 |
▼a Physics. |
| 690 | |
▼a 0574 |
| 690 | |
▼a 0605 |
| 710 | 20 |
▼a The University of Wisconsin - Madison.
▼b Medical Physics. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 80-01B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0262 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15001157
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |