• Title/Summary/Keyword: 축이탈 보정 알고리즘

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Application of Off-axis Correction Method for EPID Based IMRT QA (EPID를 사용한 세기조절방사선치료의 정도관리에 있어 축이탈 보정(Off-axis Correction)의 적용)

  • Cho, Ilsung;Kwark, Jungwon;Park, Sung Ho;Ahn, Seung Do;Jeong, Dong Hyeok;Cho, Byungchul
    • Progress in Medical Physics
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    • v.23 no.4
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    • pp.317-325
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    • 2012
  • The Varian PORTALVISION (Varian Medical Systems, US) shows significant overresponses as the off-center distance increases compared to the predicted dose. In order to correct the dose discrepancy, the off-axis correction is applied to VARIAN iX linear accelerators. The portal dose for $38{\times}28cm^2$ open field is acquired for 6 MV, 15 MV photon beams and also are predicted by PDIP algorithm under the same condition of the portal dose acquisition. The off-axis correction is applied by modifying the $40{\times}40cm^2$ diagonal beam profile data which is used for the beam profile calibration. The ratios between predicted dose and measured dose is modeled as a function of off-axis distance with the $4^{th}$ polynomial and is applied to the $40{\times}40cm^2$ diagonal beam profile data as the weight to correct measured dose by EPID detector. The discrepancy between measured dose and predicted dose is reduced from $4.17{\pm}2.76$ CU to $0.18{\pm}0.8$ CU for 6 MV photon beam and from $3.23{\pm}2.59$ CU to $0.04{\pm}0.85$ CU for 15 MV photon beam. The passing rate of gamma analysis for the pyramid fluence patten with the 4%, 4 mm criteria is improved from 98.7% to 99.1% for 6 MV photon beam, from 99.8% to 99.9% for 15 MV photon beam. IMRT QA is also performed for randomly selected Head and Neck and Prostate IMRT plans after applying the off-axis correction. The gamma passing rare is improved by 3% on average, for Head and Neck cases: $94.7{\pm}3.2%$ to $98.2{\pm}1.4%$, for Prostate cases: $95.5{\pm}2.6%$, $98.4{\pm}1.8%$. The gamma analysis criteria is 3%, 3 mm with 10% threshold. It is considered that the off-axis correction might be an effective and easily adaptable means for correcting the discrepancy between measured dose and predicted dose for IMRT QA using EPID in clinic.

The Study of Methods for Improve the Linearity of the Walking Assistant Robot to Move on Lateral Slopes (횡단경사면에서 지능형 보행보조로봇의 직진성 향상 방안 연구)

  • Lee, Won-Young;Eom, Su-Hong;Jang, Mun-Suck;Kwon, O-Sang;Lee, Eung-Hyuk
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.1
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    • pp.261-268
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    • 2013
  • In this paper, we propose the algorithm that improves the linearity of the walking assistant robot on lateral slopes. The walking assistant robot goes out of the course due to the rotational moment which is caused by the weight of the robot and the slope. To compensate this, we give the weight to each driving axle after comparing the real rotational angular velocity with the target rotational angular velocity which is entered by an user. The results of applying the algorithm to the real walking assistant robot show that the yaw axis deviation of the robot without the algorithm diverges, but the yaw axis deviation of the robot with the algorithm lies within 20cm, which can be recognized as stable. In addition, the changing rate of the course deviation is stabilized and shows no more course deviation, after moving 300cm.

A Study on The Straightness Improvement Method for Ensure Safety of Mobile Walker in Slope (경사로에서의 안정성 확보를 위한 Mobile Walker의 직진성 향상 기법에 관한 연구)

  • Lee, W.Y.;Lee, D.K.;Lee, E.H.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.8 no.3
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    • pp.187-196
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    • 2014
  • This paper suggests linearity enhancement algorithm to Ensure safety of Mobile Walker on Slope. Mobile Walker happens to get off track due to external forces from Walker's weight and the degree of the slope while slope driving. In order to compensate this, this research used the controller that estimates the external forces according to the slope of road surface and adjusts it to the motor output. Also, through comparisons between targeted rotational angular velocity which the user inputs and its velocity of the robot, algorithm was applied which applies a weight to each shaft. As a result of applying the proposed correction controller, it diverges in case of non-compensation experiments that deviates when moving, but it case of applying the ramp calibration algorithm, the deviation distance at max was within 10cm that it keeps safe driving, and change rate of deviation distance was also stabilized after 1m where no more changes occurred.

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