Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

토모테라피의 자동영상정합 분석Analysis of Automatic Rigid Image-Registration on Tomotherapy

Other Titles
Analysis of Automatic Rigid Image-Registration on Tomotherapy
Authors
김영록조광환정재홍정주영임광채김용호문성권배선현민철기김은석여승구서태석최보영민정환안재억
Issue Date
2014
Publisher
대한방사선과학회
Keywords
Tomotherapy; Image guided radiation therapy; Megavoltage computed tomography; Image-registration; 토모테라피; 영상유도방사선치료; 고에너지 전산화단층촬영; 자동영상정합
Citation
방사선기술과학, v.37, no.1, pp.37 - 47
Journal Title
방사선기술과학
Volume
37
Number
1
Start Page
37
End Page
47
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/12975
ISSN
2288-3509
Abstract
The purpose of this study was to analyze translational and rotational adjustments during automatic rigid image-registration by using different control parameters for a total of five groups on TomoTherapy (Accuray Inc, Sunnyvale, CA, USA). We selected a total of 50 patients and classified them in five groups (brain, head-and-neck, lung, abdomen and pelvic) and used a total of 500 megavoltage computed tomography (MVCT) image sets for the analysis. From this we calculated the overall mean value(M) for systematic and random errors after applying the different control parameters. After randomization of the patients into the five groups, we found that the overall mean value varied according to three techniques and resolutions. The deviation for the lung, abdomen and pelvic groups was approximately greater than the deviation for the brain and head-and-neck groups in all adjustments. Overall, using a “full-image” produces smaller deviations in the rotational adjustments. We found that rotational adjustment has deviations with distinctly different control parameters. We concluded that using a combination of the “full-image” technique and “standard” resolution will be helpful in assisting with patients’ repositioning and in correcting for set-up errors prior to radiotherapy on TomoTherapy.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Medicine > Department of Radiation Oncology > 1. Journal Articles
College of Medicine > Department of Radiation Oncology > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Yeo, Seung Gu photo

Yeo, Seung Gu
College of Medicine (Department of Radiation Oncology)
Read more

Altmetrics

Total Views & Downloads

BROWSE