• Title/Summary/Keyword: Inhomogeneity correction

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Water-Fat Imaging with Automatic Field Inhomogeneity Correction Using Joint Phase Magnitude Density Function at Low Field MRI (저자장 자기공명영상에서 위상-크기 결합 밀도 함수를 이용한 자동 불균일 자장 보정 물-지방 영상 기법)

  • Kim, Pan-Ki;Ahn, Chang-Beom
    • Investigative Magnetic Resonance Imaging
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    • v.15 no.1
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    • pp.57-66
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    • 2011
  • Purpose : A new inhomogeneity correction method based on two-point Dixon sequence is proposed to obtain water and fat images at 0.35T, low field magnetic resonance imaging (MRI) system. Materials and Methods : Joint phase-magnitude density function (JPMF) is obtained from the in-phase and out-of-phase images by the two-point Dixon method. The range of the water signal is adjusted from the JPMF, and 3D inhomogeneity map is obtained from the phase of corresponding water volume. The 3D inhomogeneity map is used to correct the inhomogeneity field iteratively. Results : The proposed water-fat imaging method was successfully applied to various organs. The proposed 3D inhomogeneity correction algorithm provides good performances in overall multi-slice images. Conclusion : The proposed water-fat separation method using JPMF is robust to field inhomogeneity. Three dimensional inhomogeneity map and the iterative inhomogeneity correction algorithm improve water and fat imaging substantially.

Estimation of Inhomogeneity Correction Factor in Small Field Dosimetry (소조사면에서의 불균질 물질 보정 계산의 평가)

  • Shin, Hun-Joo;Kang, Young-Nam;Jang, Ji-Sun;Seo, Jae-Hyuk;Jung, Ji-Young;Choi, Byung-Ock;Choi, Ihl-Bohng;Lee, Dong-Joon;Kwon, Soo-Il
    • Progress in Medical Physics
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    • v.20 no.4
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    • pp.260-268
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    • 2009
  • In this study, we estimated inhomogeneity correction factor in small field. And, we evaluated accuracy of treatment planning and measurement data which applied inhomogeneity correction factor or not. We developed the Inhomogeneity Correction Phantom (ICP) for insertion of inhomogeneity materials. The inhomogeneity materials were 12 types in each different electron density. This phantom is able to adapt the EBT film and 0.125 cc ion chamber for measurement of dose distribution and point dose. We evaluated comparison of planning and measurement data using ICP. When we applied to inhomogeneity correction factor or not, the average difference was 1.63% and 10.05% in each plan and film measurement data. And, the average difference of dose distribution was 10.09% in each measurement film. And the average difference of point dose was 0.43% and 2.09% in each plan and measurement data. In conclusion, if we did not apply the inhomogeneity correction factor in small field, it shows more great difference in measurement data. The planning system using this study shows good result for correction of inhomogeneity materials. In radiosurgery using small field, we should be correct the inhomogeneity correction factor, more exactly.

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Effect of Inhomogeneity correction for lung volume model in TPS (Lnug Volume을 모델로 한 방사선치료계획 시 불균질 조직 보정에 따른 효과)

  • Chung SeYoung;Lee SangRok;Kim YoungBum;Kwon YoungHo
    • The Journal of Korean Society for Radiation Therapy
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    • v.16 no.1
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    • pp.57-65
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    • 2004
  • Introduction : The phantom that includes high density materials such as steel was custom-made to fix lung and bone in order to evaluation inhomogeneity correction at the time of conducting radiation therapy to treat lung cancer. Using this, values resulting from the inhomogeneous correction algorithm are compared on the 2 and 3 dimensional radiation therapy planning systems. Moreover, change in dose calculation was evaluated according to inhomogeneous by comparing with the actual measurement. Materials and Methods : As for the image acquisition, inhomogeneous correction phantom(Pig's vertebra, steel(8.21g/cm3), cork(0.23 g/cm3)) that was custom-made and the CT(Volume zoom, Siemens, Germany) were used. As for the radiation therapy planning system, Marks Plan(2D) and XiO(CMS, USA, 3D) were used. To compare with the measurement value, linear accelerator(CL/1800, Varian, USA) and ion chamber were used. Image, obtained from the CT was used to obtain point dose and dose distribution from the region of interest (ROI) while on the radiation therapy planning device. After measurement was conducted under the same conditions, value on the treatment planning device and measured value were subjected to comparison and analysis. And difference between the resulting for the evaluation on the use (or non-use) of inhomogeneity correction algorithm, and diverse inhomogeneity correction algorithm that is included in the radiation therapy planning device was compared as well. Results : As result of comparing the results of measurement value on the region of interest within the inhomogeneity correction phantom and the value that resulted from the homogeneous and inhomogeneous correction, gained from the therapy planning device, margin of error of the measurement value and inhomogeneous correction value at the location 1 of the lung showed $0.8\%$ on 2D and $0.5\%$ on 3D. Margin of error of the measurement value and inhomogeneous correction value at the location 1 of the steel showed $12\%$ on 2D and $5\%$ on 3D, however, it is possible to see that the value that is not correction and the margin of error of the measurement value stand at $16\%$ and $14\%$, respectively. Moreover, values of the 3D showed lower margin of error compared to 2D. Conclusion : Revision according to the density of tissue must be executed during radiation therapy planning. To ensure a more accurate planning, use of 3D planning system is recommended more so than the 2D Planning system to ensure a more accurate revision on the therapy plan. Moreover, 3D Planning system needs to select and use the most accurate and appropriate inhomogeneous correction algorithm through actual measurement. In addition, comparison and analysis through TLD or film dosimetry are needed.

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The Impact of Tissue Inhomogeneity Corrections in the Treatment of Prostate Cancer with Intensity-Modulated Radiation Therapy (전립선암의 세기조절 방사선 치료시 밀도보정의 효과)

  • Han Youngyih;Park Won;Huh Seung Jae
    • Progress in Medical Physics
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    • v.15 no.3
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    • pp.149-155
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    • 2004
  • Purpose: To investigate the effects of tissue inhomogeneity corrections on the dose delivered to prostate cancer patients treated with Intensity-Modulated Radiation Therapy (IMRT). Methods and Materials: For five prostate cancer patients, IMRT treatment plans were generated using 6 MV or 10 MV X-rays. In each plan, seven equally spaced ports of photon beams were directed to the isocenter, neglecting the tissue heterogeneity in the body. The dose at the isocenter, mean dose, maximum dose, minimum dose and volume that received more than 95% of the isocenter dose in the planning target volume ( $V_{p>95%}$) were measured. The maximum doses to the rectum and the bladder, and the volumes that received more than 50, 75 and 90% of the prescribed dose were measured. Treatment plans were then recomputed using tissue inhomogeneity correction maintaining the intensity profiles and monitor units of each port. The prescription point dose and other dosimetric parameters were remeasured. Results: The inhomogeneity correction reduced the prescription point dose by an average 4.9 and 4.0% with 6 and 10 MV X-rays, respectively. The average reductions of the $V_{p>95%}$ were 0.8 and 0.9% with the 6 and 10 MV X-rays, respectively. The mean doses in the PTV were reduced by an average of 4.2 and 3.4% with the 6 and 10 MV X-rays, respectively. The irradiated volume parameters in the rectum and bladder were less decreased; less than 2.1 % (1.2%) of the reduction in the rectum (bladder). The average reductions in the mean dose were 1.0 and 0.5% in the rectum and bladder, respectively. Conclusions: Neglect of tissue inhomogeneity in the IMRT treatment of prostate cancer gives rise to a notable overestimation of the dose delivered to the target, whereas the impact of tissue inhomogeneity correction to the surrounding critical organs is less significant.

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Simultaneous Unwrapping Phase and Error Recovery from Inhomogeneity (SUPER) for Quantitative Susceptibility Mapping of the Human Brain

  • Yang, Young-Joong;Yoon, Jong-Hyun;Baek, Hyun-Man;Ahn, Chang-Beom
    • Investigative Magnetic Resonance Imaging
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    • v.22 no.1
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    • pp.37-49
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    • 2018
  • Purpose: The effect of global inhomogeneity on quantitative susceptibility mapping (QSM) was investigated. A technique referred to as Simultaneous Unwrapping Phase with Error Recovery from inhomogeneity (SUPER) is suggested as a preprocessing to QSM to remove global field inhomogeneity-induced phase by polynomial fitting. Materials and Methods: The effect of global inhomogeneity on QSM was investigated by numerical simulations. Three types of global inhomogeneity were added to the tissue susceptibility phase, and the root mean square error (RMSE) in the susceptibility map was evaluated. In-vivo QSM imaging with volunteers was carried out for 3.0T and 7.0T MRI systems to demonstrate the efficacy of the proposed method. Results: The SUPER technique removed harmonic and non-harmonic global phases. Previously only the harmonic phase was removed by the background phase removal method. The global phase contained a non-harmonic phase due to various experimental and physiological causes, which degraded a susceptibility map. The RMSE in the susceptibility map increased under the influence of global inhomogeneity; while the error was consistent, irrespective of the global inhomogeneity, if the inhomogeneity was corrected by the SUPER technique. In-vivo QSM imaging with volunteers at 3.0T and 7.0T MRI systems showed better definition in small vascular structures and reduced fluctuation and non-uniformity in the frontal lobes, where field inhomogeneity was more severe. Conclusion: Correcting global inhomogeneity using the SUPER technique is an effective way to obtain an accurate susceptibility map on QSM method. Since the susceptibility variations are small quantities in the brain tissue, correction of the inhomogeneity is an essential element for obtaining an accurate QSM.

Gamma correction FCM algorithm with conditional spatial information for image segmentation

  • Liu, Yang;Chen, Haipeng;Shen, Xuanjing;Huang, Yongping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.9
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    • pp.4336-4354
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    • 2018
  • Fuzzy C-means (FCM) algorithm is a most usually technique for medical image segmentation. But conventional FCM fails to perform well enough on magnetic resonance imaging (MRI) data with the noise and intensity inhomogeneity (IIH). In the paper, we propose a Gamma correction conditional FCM algorithm with spatial information (GcsFCM) to solve this problem. Firstly, the pre-processing, Gamma correction, is introduced to enhance the details of images. Secondly, the spatial information is introduced to reduce the effect of noise. Then we introduce the effective neighborhood mechanism into the local space information to improve the robustness for the noise and inhomogeneity. And the mechanism describes the degree of participation in generating local membership values and building clusters. Finally, the adjustment mechanism and the spatial information are combined into the weighted membership function. Experimental results on four image volumes with noise and IIH indicate that the proposed GcsFCM algorithm is more effective and robust to noise and IIH than the FCM, sFCM and csFCM algorithms.