語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Predictive feedback control of the t...
~
Virginia Commonwealth University.
FindBook
Google Book
Amazon
博客來
Predictive feedback control of the treatment couch for tumor motion compensation during radiotherapy.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Predictive feedback control of the treatment couch for tumor motion compensation during radiotherapy./
作者:
Tchoupo, Guy Narcisse.
面頁冊數:
80 p.
附註:
Adviser: Alen Docef.
Contained By:
Dissertation Abstracts International69-08B.
標題:
Biophysics, Medical. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3326672
ISBN:
9780549780304
Predictive feedback control of the treatment couch for tumor motion compensation during radiotherapy.
Tchoupo, Guy Narcisse.
Predictive feedback control of the treatment couch for tumor motion compensation during radiotherapy.
- 80 p.
Adviser: Alen Docef.
Thesis (Ph.D.)--Virginia Commonwealth University, 2008.
In radiation therapy, tumor motion induced by the patient's respiration may lead to significant differences between the planned and delivered radiation dose. Compensating for tumor motion is therefore crucial for accurate and efficient treatment. In this dissertation, we study a real-time compensation method through predictive feedback control of the treatment couch.
ISBN: 9780549780304Subjects--Topical Terms:
1017681
Biophysics, Medical.
Predictive feedback control of the treatment couch for tumor motion compensation during radiotherapy.
LDR
:03317nmm 2200301 a 45
001
862658
005
20100721
008
100721s2008 ||||||||||||||||| ||eng d
020
$a
9780549780304
035
$a
(UMI)AAI3326672
035
$a
AAI3326672
040
$a
UMI
$c
UMI
100
1
$a
Tchoupo, Guy Narcisse.
$3
1030498
245
1 0
$a
Predictive feedback control of the treatment couch for tumor motion compensation during radiotherapy.
300
$a
80 p.
500
$a
Adviser: Alen Docef.
500
$a
Source: Dissertation Abstracts International, Volume: 69-08, Section: B, page: 4949.
502
$a
Thesis (Ph.D.)--Virginia Commonwealth University, 2008.
520
$a
In radiation therapy, tumor motion induced by the patient's respiration may lead to significant differences between the planned and delivered radiation dose. Compensating for tumor motion is therefore crucial for accurate and efficient treatment. In this dissertation, we study a real-time compensation method through predictive feedback control of the treatment couch.
520
$a
Conventional approaches (margin expansion, breath-holds, gating) have substantial drawbacks. Real-time tracking has the potential to overcome these limitations. A real challenge in real-time tumor motion tracking approach is the presence of delays in the treatment system. In this dissertation we studied a new real-time tracking method, which compensate the tumor motion through feedback control of the treatment couch. This approach consists of first applying a predictor to overcome the delays and then the predicted signal is used as the reference for the controlled couch. In order to handle the irregularities of the breathing signals, we developed and evaluated optimized versions of the Least Mean Squares (LMS), the Recursive Least Squares (RLS) algorithm, and Neural Networks (NN). Additionally, the use of a Nonlinear Set Membership (NSM) algorithm for prediction of human breathing was investigated. This approach does not require the choice of a predefined functional form for the predictor. The NSM approach resulted in better prediction performance compared to optimized LMS, RLS, and NN. In addition the convergence issue appeared to be completely solved. Considering the predicted signal to be the tracking reference, we then pursued the problem of predictive feedback real-time tumor motion tracking, by designing the couch controller following two different approaches, a pole placement method and an optimal control control method. The pole placement method was found to be insufficiently robust due to inadequate stability margin. The optimal approach appeared to be more robust and gave optimal tracking results. The real-time tracking approach was evaluated by performing simulation using nine real clinical signals. Only two of the nine cases appeared to have tracking error samples exceeding 0.3 cm and at most 1.14% of the tracking error samples exceeded the 0.3 cm threshold. These results show the validity of the proposed approach as a real-time tumor motion tracking solution.
590
$a
School code: 2383.
650
4
$a
Biophysics, Medical.
$3
1017681
650
4
$a
Engineering, Electronics and Electrical.
$3
626636
650
4
$a
Health Sciences, Radiology.
$3
1019076
690
$a
0544
690
$a
0574
690
$a
0760
710
2
$a
Virginia Commonwealth University.
$3
1018010
773
0
$t
Dissertation Abstracts International
$g
69-08B.
790
$a
2383
790
1 0
$a
Docef, Alen,
$e
advisor
791
$a
Ph.D.
792
$a
2008
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3326672
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9076038
電子資源
11.線上閱覽_V
電子書
EB W9076038
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入