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RISS 인기검색어
- 검색키워드
- 저자 : Lee Jiseoc (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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Lee, Donghyeon,Lee, Jiseoc,Kim, Hyoyi,Lee, Taewon,Soh, Jeongtae,Park, Miran,Kim, Changhwan,Lee, Yeon Ju,Cho, Seungryong IEEE 2017 IEEE transactions on medical imaging Vol.36 No.12
<P>A single-scan dual-energy low-dose cone-beam CT (CBCT) imaging technique that exploits a multi-slit filter is proposed in this paper. The multi-slit filter installed between the x-ray source and the scanned object is reciprocated during a scan. The x-ray beams through the slits would generate relatively low-energy x-ray projection data, while the filtered beams would make high-energy projection data. An iterative image reconstruction algorithm that uses an adaptive-steepest-descent method to minimize image total-variation under the constraint of data fidelity was applied to reconstructing the image from the low-energy projection data. Since the high-energy projection data suffer from a substantially high noise level due to the beam filtration, we have developed a new algorithm that exploits the joint sparsity between the low-and high-energy CT images for image reconstruction of the high-energy CT image. The proposed image reconstruction algorithm uses a gradient magnitude image (GMI) of the low-energy CT image by regularizing the difference of GMIs of the low-and high-energy CT images to be minimized. The feasibility of the proposed technique has been demonstrated by the use of various phantoms in the experimental CBCT setup. Furthermore, based on the proposed dual-energy imaging, a material differentiation was performed and its potential utility has been shown. The proposed imaging technique produced promising results for its potential application to a low-dose single-scan dual-energy CBCT.</P>
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Sparse-view proton computed tomography using modulated proton beams : Sparse-view proton CT
Lee, Jiseoc,Kim, Changhwan,Min, Byungjun,Kwak, Jungwon,Park, Seyjoon,Lee, Se Byeong,Park, Sungyong,Cho, Seungryong Published for the American Association of Physicis 2015 Medical physics Vol.42 No.2
<P>Proton imaging that uses a modulated proton beam and an intensity detector allows a relatively fast image acquisition compared to the imaging approach based on a trajectory tracking detector. In addition, it requires a relatively simple implementation in a conventional proton therapy equipment. The model of geometric straight ray assumed in conventional computed tomography (CT) image reconstruction is however challenged by multiple-Coulomb scattering and energy straggling in the proton imaging. Radiation dose to the patient is another important issue that has to be taken care of for practical applications. In this work, the authors have investigated iterative image reconstructions after a deconvolution of the sparsely view-sampled data to address these issues in proton CT.</P>
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Improving image accuracy of region‐of‐interest in cone‐beam CT using prior image
Lee, Jiseoc,Kim, Jin Sung,Cho, Seungryong John Wiley and Sons Inc. 2014 Journal of applied clinical medical physics Vol.15 No.2
<P>In diagnostic follow‐ups of diseases, such as calcium scoring in kidney or fat content assessment in liver using repeated CT scans, quantitatively accurate and consistent CT values are desirable at a low cost of radiation dose to the patient. Region‐of‐interest (ROI) imaging technique is considered a reasonable dose reduction method in CT scans for its shielding geometry outside the ROI. However, image artifacts in the reconstructed images caused by missing data outside the ROI may degrade overall image quality and, more importantly, can decrease image accuracy of the ROI substantially. In this study, we propose a method to increase image accuracy of the ROI and to reduce imaging radiation dose via utilizing the outside ROI data from prior scans in the repeated CT applications. We performed both numerical and experimental studies to validate our proposed method. In a numerical study, we used an XCAT phantom with its liver and stomach changing their sizes from one scan to another. Image accuracy of the liver has been improved as the error decreased from 44.4 HU to −0.1 HU by the proposed method, compared to an existing method of data extrapolation to compensate for the missing data outside the ROI. Repeated cone‐beam CT (CBCT) images of a patient who went through daily CBCT scans for radiation therapy were also used to demonstrate the performance of the proposed method experimentally. The results showed improved image accuracy inside the ROI. The magnitude of error decreased from −73.2 HU to 18 HU, and effectively reduced image artifacts throughout the entire image.</P><P>PACS number: 87.57. Q‐</P>
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