The Experts below are selected from a list of 54 Experts worldwide ranked by ideXlab platform
T Mao - One of the best experts on this subject based on the ideXlab platform.
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we G 207 07 iterative ct shadinG correction method with no prior information
Medical Physics, 2015Co-Authors: T Mao, S Xie, Ke Sheng, T NiuAbstract:Purpose: ShadinG artifacts are caused by scatter contamination, beam hardeninG effects and other non-ideal imaGinG condition. Our Purpose is to propose a novel and General correction framework to eliminate low-frequency shadinG artifacts in CT imaGinG (e.G., cone-beam CT, low-kVp CT) without relyinG on prior information. Methods: Our method applies General knowledGe of the relatively uniform CT number distribution in one tissue component. ImaGe seGmentation is applied to construct template imaGe where each structure is filled with the same CT number of that specific tissue. By subtractinG the ideal template from CT imaGe, the residual from various error sources are Generated. Since the forward projection is an inteGration process, the non-continuous low-frequency shadinG artifacts in the imaGe become continuous and low-frequency siGnals in the line inteGral. Residual imaGe is thus forward projected and its line inteGral is filtered usinG Savitzky-Golay filter to estimate the error. A compensation map is reconstructed on the error usinG standard FDK alGorithm and added to the oriGinal imaGe to obtain the shadinG corrected one. Since the seGmentation is not accurate on shaded CT imaGe, the proposed scheme is iterated until the variation of residual imaGe is minimized. Results: The proposed method is evaluated on a Catphan600 phantom, a pelvic patient and a CT anGioGraphy scan for carotid artery assessment. Compared to the one without correction, our method reduces the overall CT number error from >200 HU to be <35 HU and increases the spatial uniformity by a factor of 1.4. Conclusion: We propose an effective iterative alGorithm for shadinG correction in CT imaGinG. BeinG different from existinG alGorithms, our method is only assisted by General anatomical and physical information in CT imaGinG without relyinG on prior knowledGe. Our method is thus practical and attractive as a General solution to CT shadinG correction. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National HiGh TechnoloGy Research and Development ProGram of China (863 proGram, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and TechnoloGy.
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we G 207 09 a practical bowtie rinG artifact correction alGorithm for cone beam ct
Medical Physics, 2015Co-Authors: T Mao, S Xie, Ke Sheng, T NiuAbstract:Purpose: Shaded rinG artifact in cone-beam CT (CBCT) is caused by scatter contamination from bowtie-modulated primary beam and presents a unique rinG pattern in CBCT imaGe. Previous shadinG correction methods, which suppress the artifact as conventional scatter correction in projection domain, are complicated due to the non-trivial scatter estimation. In this work, we propose a practical and readily implementable alGorithm to correct for the severe shaded rinG in CBCT without relyinG on prior information and directly in imaGe domain. Methods: Due to the correlation between the rinG pattern and bowtie modulator, an initial bowtie mask was reconstructed from bowtie-modulated air-scan projections as if they were acquired from a flat-field exposure penetratinG the bowtie modulator. The shape of the bowtie mask matches well with that of the shaded rinG in CBCT, while its intensity needs to be scaled to fully compensate for the shadinG rinG. To find a correct scalinG factor, we start from the anatomical knowledGe that the same tissue has comparable CT number. This knowledGe indicates a sharp peak in histoGram of that specific tissue. One way to achieve this Goal is to maximize the peak value of the histoGram of that tissue. The above concept is formulated as a mathematical optimization problem which is solved usinG a standard Simplex method. The shaded rinG artifact in CBCT is finally corrected for by addinG a scaled bowtie mask. Results: The proposed method is evaluated on one pelvis patient. Severe shaded rinG artifact is Greatly suppressed. Our method reduces the CT number error from >200 HU to be ∼50 HU, and increases the spatial uniformity by 1.3 times. Conclusion: We propose a practical imaGe-domain alGorithm for shaded rinG artifact correction in CBCT. It is computationally efficient and does not rely on prior knowledGe. It is thus attractive for clinical use. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National HiGh TechnoloGy Research and Development ProGram of China (863 proGram, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and TechnoloGy.
S Xie - One of the best experts on this subject based on the ideXlab platform.
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we G 207 07 iterative ct shadinG correction method with no prior information
Medical Physics, 2015Co-Authors: T Mao, S Xie, Ke Sheng, T NiuAbstract:Purpose: ShadinG artifacts are caused by scatter contamination, beam hardeninG effects and other non-ideal imaGinG condition. Our Purpose is to propose a novel and General correction framework to eliminate low-frequency shadinG artifacts in CT imaGinG (e.G., cone-beam CT, low-kVp CT) without relyinG on prior information. Methods: Our method applies General knowledGe of the relatively uniform CT number distribution in one tissue component. ImaGe seGmentation is applied to construct template imaGe where each structure is filled with the same CT number of that specific tissue. By subtractinG the ideal template from CT imaGe, the residual from various error sources are Generated. Since the forward projection is an inteGration process, the non-continuous low-frequency shadinG artifacts in the imaGe become continuous and low-frequency siGnals in the line inteGral. Residual imaGe is thus forward projected and its line inteGral is filtered usinG Savitzky-Golay filter to estimate the error. A compensation map is reconstructed on the error usinG standard FDK alGorithm and added to the oriGinal imaGe to obtain the shadinG corrected one. Since the seGmentation is not accurate on shaded CT imaGe, the proposed scheme is iterated until the variation of residual imaGe is minimized. Results: The proposed method is evaluated on a Catphan600 phantom, a pelvic patient and a CT anGioGraphy scan for carotid artery assessment. Compared to the one without correction, our method reduces the overall CT number error from >200 HU to be <35 HU and increases the spatial uniformity by a factor of 1.4. Conclusion: We propose an effective iterative alGorithm for shadinG correction in CT imaGinG. BeinG different from existinG alGorithms, our method is only assisted by General anatomical and physical information in CT imaGinG without relyinG on prior knowledGe. Our method is thus practical and attractive as a General solution to CT shadinG correction. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National HiGh TechnoloGy Research and Development ProGram of China (863 proGram, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and TechnoloGy.
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we G 207 09 a practical bowtie rinG artifact correction alGorithm for cone beam ct
Medical Physics, 2015Co-Authors: T Mao, S Xie, Ke Sheng, T NiuAbstract:Purpose: Shaded rinG artifact in cone-beam CT (CBCT) is caused by scatter contamination from bowtie-modulated primary beam and presents a unique rinG pattern in CBCT imaGe. Previous shadinG correction methods, which suppress the artifact as conventional scatter correction in projection domain, are complicated due to the non-trivial scatter estimation. In this work, we propose a practical and readily implementable alGorithm to correct for the severe shaded rinG in CBCT without relyinG on prior information and directly in imaGe domain. Methods: Due to the correlation between the rinG pattern and bowtie modulator, an initial bowtie mask was reconstructed from bowtie-modulated air-scan projections as if they were acquired from a flat-field exposure penetratinG the bowtie modulator. The shape of the bowtie mask matches well with that of the shaded rinG in CBCT, while its intensity needs to be scaled to fully compensate for the shadinG rinG. To find a correct scalinG factor, we start from the anatomical knowledGe that the same tissue has comparable CT number. This knowledGe indicates a sharp peak in histoGram of that specific tissue. One way to achieve this Goal is to maximize the peak value of the histoGram of that tissue. The above concept is formulated as a mathematical optimization problem which is solved usinG a standard Simplex method. The shaded rinG artifact in CBCT is finally corrected for by addinG a scaled bowtie mask. Results: The proposed method is evaluated on one pelvis patient. Severe shaded rinG artifact is Greatly suppressed. Our method reduces the CT number error from >200 HU to be ∼50 HU, and increases the spatial uniformity by 1.3 times. Conclusion: We propose a practical imaGe-domain alGorithm for shaded rinG artifact correction in CBCT. It is computationally efficient and does not rely on prior knowledGe. It is thus attractive for clinical use. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National HiGh TechnoloGy Research and Development ProGram of China (863 proGram, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and TechnoloGy.
Ke Sheng - One of the best experts on this subject based on the ideXlab platform.
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we G 207 07 iterative ct shadinG correction method with no prior information
Medical Physics, 2015Co-Authors: T Mao, S Xie, Ke Sheng, T NiuAbstract:Purpose: ShadinG artifacts are caused by scatter contamination, beam hardeninG effects and other non-ideal imaGinG condition. Our Purpose is to propose a novel and General correction framework to eliminate low-frequency shadinG artifacts in CT imaGinG (e.G., cone-beam CT, low-kVp CT) without relyinG on prior information. Methods: Our method applies General knowledGe of the relatively uniform CT number distribution in one tissue component. ImaGe seGmentation is applied to construct template imaGe where each structure is filled with the same CT number of that specific tissue. By subtractinG the ideal template from CT imaGe, the residual from various error sources are Generated. Since the forward projection is an inteGration process, the non-continuous low-frequency shadinG artifacts in the imaGe become continuous and low-frequency siGnals in the line inteGral. Residual imaGe is thus forward projected and its line inteGral is filtered usinG Savitzky-Golay filter to estimate the error. A compensation map is reconstructed on the error usinG standard FDK alGorithm and added to the oriGinal imaGe to obtain the shadinG corrected one. Since the seGmentation is not accurate on shaded CT imaGe, the proposed scheme is iterated until the variation of residual imaGe is minimized. Results: The proposed method is evaluated on a Catphan600 phantom, a pelvic patient and a CT anGioGraphy scan for carotid artery assessment. Compared to the one without correction, our method reduces the overall CT number error from >200 HU to be <35 HU and increases the spatial uniformity by a factor of 1.4. Conclusion: We propose an effective iterative alGorithm for shadinG correction in CT imaGinG. BeinG different from existinG alGorithms, our method is only assisted by General anatomical and physical information in CT imaGinG without relyinG on prior knowledGe. Our method is thus practical and attractive as a General solution to CT shadinG correction. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National HiGh TechnoloGy Research and Development ProGram of China (863 proGram, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and TechnoloGy.
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we G 207 09 a practical bowtie rinG artifact correction alGorithm for cone beam ct
Medical Physics, 2015Co-Authors: T Mao, S Xie, Ke Sheng, T NiuAbstract:Purpose: Shaded rinG artifact in cone-beam CT (CBCT) is caused by scatter contamination from bowtie-modulated primary beam and presents a unique rinG pattern in CBCT imaGe. Previous shadinG correction methods, which suppress the artifact as conventional scatter correction in projection domain, are complicated due to the non-trivial scatter estimation. In this work, we propose a practical and readily implementable alGorithm to correct for the severe shaded rinG in CBCT without relyinG on prior information and directly in imaGe domain. Methods: Due to the correlation between the rinG pattern and bowtie modulator, an initial bowtie mask was reconstructed from bowtie-modulated air-scan projections as if they were acquired from a flat-field exposure penetratinG the bowtie modulator. The shape of the bowtie mask matches well with that of the shaded rinG in CBCT, while its intensity needs to be scaled to fully compensate for the shadinG rinG. To find a correct scalinG factor, we start from the anatomical knowledGe that the same tissue has comparable CT number. This knowledGe indicates a sharp peak in histoGram of that specific tissue. One way to achieve this Goal is to maximize the peak value of the histoGram of that tissue. The above concept is formulated as a mathematical optimization problem which is solved usinG a standard Simplex method. The shaded rinG artifact in CBCT is finally corrected for by addinG a scaled bowtie mask. Results: The proposed method is evaluated on one pelvis patient. Severe shaded rinG artifact is Greatly suppressed. Our method reduces the CT number error from >200 HU to be ∼50 HU, and increases the spatial uniformity by 1.3 times. Conclusion: We propose a practical imaGe-domain alGorithm for shaded rinG artifact correction in CBCT. It is computationally efficient and does not rely on prior knowledGe. It is thus attractive for clinical use. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National HiGh TechnoloGy Research and Development ProGram of China (863 proGram, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and TechnoloGy.
Lei Xing - One of the best experts on this subject based on the ideXlab platform.
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tu G 207 00 emerGinG applications of x ray imaGinG
Medical Physics, 2015Co-Authors: Lei XingAbstract:Last few years has witnessed the development of novel of X-ray imaGinG modalities, such as spectral CT, phase contrast CT, and X-ray acoustic/fluorescence/luminescence imaGinG. This symposium will present the recent advances of these emerGinG X-ray imaGinG modalities and update the attendees with knowledGe in various related topics, includinG X-ray photon-countinG detectors, X-ray physics underlyinG the emerGinG applications beyond the traditional X-ray imaGinG, imaGe reconstruction for the novel modalities, characterization and evaluation of the systems, and their practical implications. In addition, the concept and practical aspects of X-ray activatable tarGeted nanoparticles for molecular X-ray imaGinG will be discussed in the context of X-ray fluorescence and luminescence CT. LearninG Objectives: 1. Present backGround knowledGe of various emerGinG X-ray imaGinG techniques, such as spectral CT, phase contrast CT and X-ray fluorescence/luminescence CT. 2. Discuss the practical need, technical aspects and current status of the emerGinG X-ray imaGinG modalities. 3. Describe utility and future impact of the new Generation of X-ray imaGinG applications.
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tu G 207 03 hiGh spatial resolution and hiGh sensitivity x ray fluorescence imaGinG
Medical Physics, 2015Co-Authors: Lei XingAbstract:Last few years has witnessed the development of novel of X-ray imaGinG modalities, such as spectral CT, phase contrast CT, and X-ray acoustic/fluorescence/luminescence imaGinG. This symposium will present the recent advances of these emerGinG X-ray imaGinG modalities and update the attendees with knowledGe in various related topics, includinG X-ray photon-countinG detectors, X-ray physics underlyinG the emerGinG applications beyond the traditional X-ray imaGinG, imaGe reconstruction for the novel modalities, characterization and evaluation of the systems, and their practical implications. In addition, the concept and practical aspects of X-ray activatable tarGeted nanoparticles for molecular X-ray imaGinG will be discussed in the context of X-ray fluorescence and luminescence CT. LearninG Objectives: 1. Present backGround knowledGe of various emerGinG X-ray imaGinG techniques, such as spectral CT, phase contrast CT and X-ray fluorescence/luminescence CT. 2. Discuss the practical need, technical aspects and current status of the emerGinG X-ray imaGinG modalities. 3. Describe utility and future impact of the new Generation of X-ray imaGinG applications.
Xun Jia - One of the best experts on this subject based on the ideXlab platform.
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we G 207 08 imaGinG dose reduction and scatter removal in cone beam ct via random undersamplinG a simulation study
Medical Physics, 2015Co-Authors: Chenyang Shen, Liang Chen, Zhen Tian, T Zeng, Yifei Lou, L Zhu, Xun JiaAbstract:Purpose: Cone-beam CT (CBCT) is widely used in imaGe-Guided radiation therapy. The hiGh imaGinG dose from repeated uses is a clinical concern and its imaGe quality is impeded by a larGe amount of scattered photons. We propose to solve these two problems via a random undersamplinG method. We have performed Monte Carlo (MC) simulation studies for an initial test of the method. Methods: We propose to place a movinG beam blocker with a random blockinG pattern in front of the x-ray source. It blocks a projection with a random pattern, which varies amonG projections. Scatter siGnal is measured in the deliberately created shadows, which is further interpolated to the entire projection. After removinG the interpolated scatter from the total siGnal in the un-blocked area, the cleaned data were used for CBCT reconstruction under a TiGht Frame (TF) based iterative method. The random samplinG yields a projection matrix that has a better numerical property compared to reGular undersamplinG, permittinG better imaGe reconstruction. Results: 360 CBCT projections of a head-and-neck cancer patient were Generated via MC simulations. We first reconstructed CBCTs usinG 90 full projections with only primary data. The RMS error was 16%. When scattered photons were included in the projection, reduced contrast was observed and the RMS error was 22%. In our proposed method, 360 projections were used, but each of them was randomly blocked by 75% of pixels. Scatter estimation and was performed and the corrected data were used in reconstruction, yieldinG a reconstruction error of 15%. In these two approaches, the imaGinG doses were both reduced by ∼75% compared to a full scan with 360 unblocked projections. Conclusion: we proposed a method to solve the imaGinG dose and scatter problem in CBCT in a unified manner. Preliminary simulation studies demonstrated its efficacy.
