The Experts below are selected from a list of 30504 Experts worldwide ranked by ideXlab platform
Wusheng Lu - One of the best experts on this subject based on the ideXlab platform.
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separate joint optimization of error feedback and Coordinate Transformation for roundoff noise minimization in two dimensional state space digital filters
IEEE Transactions on Signal Processing, 2003Co-Authors: Takao Hinamoto, K Higashi, Wusheng LuAbstract:This paper is concerned with the minimization of roundoff noise subject to l/sub 2/-norm dynamic-range scaling constraints in two-dimensional (2-D) state-space digital filters. Two methods are proposed, with the first one using error feedback alone and the second one using joint error feedback and Coordinate Transformation optimization. In the first method, several techniques for the determination of optimal full-scale, block-diagonal, diagonal, and scalar error-feedback matrices for a given 2-D state-space digital filter are proposed. In the second method, an iterative approach for minimizing the roundoff noise under l/sub 2/-norm dynamic-range scaling constraints is developed by jointly optimizing a scalar error-feedback matrix and a Coordinate Transformation matrix, which may be regarded as an alternative approach to the conventional method for synthesizing the optimal 2-D filter structure with minimum roundoff noise. An analytical method for the joint optimization of a general error-feedback matrix and a Coordinate Transformation matrix under the scaling constraints is also proposed. A numerical example is presented to illustrate the utility of the proposed techniques.
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joint optimization of error feedback and Coordinate Transformation for roundoff noise minimization in 2d state space digital filters
International Symposium on Circuits and Systems, 2003Co-Authors: Takao Hinamoto, H Ohnishi, Wusheng LuAbstract:An iterative approach for joint optimization of a scalar error-feedback matrix and a Coordinate Transformation matrix is developed to minimize the roundoff noise subject to the l/sub 2/-norm dynamic-range scaling constraints. When the iterative algorithm converges and the optimal Coordinate Transformation matrix is obtained, the diagonal error-feedback matrix is derived to minimize the noise gain in the optimal state-space realization. This diagonal error-feedback matrix enables one to produce more reduction of the noise gain. Finally, a numerical example is given to illustrate the utility of the proposed technique.
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roundoff noise minimization of state space digital filters using separate and joint error feedback Coordinate Transformation optimization
IEEE Transactions on Circuits and Systems I-regular Papers, 2003Co-Authors: Takao Hinamoto, H Ohnishi, Wusheng LuAbstract:This paper investigates the problem of minimizing roundoff noise under l/sub 2/-norm dynamic-range scaling constraints in state-space digital fibers by means of error feedback as well as joint error feedback/Coordinate Transformation optimization. First, several techniques, for the determination of optimal full-scale, diagonal, and scalar error-feedback matrices for a given state-space digital filter are proposed, where three realization schemes, namely, the general state-space realization, input-balanced realization, and optimal realization in the sense of Hwang-Mullis-Roberts are examined. Furthermore, an iterative approach is developed for jointly optimizing a scalar error-feedback matrix and a Coordinate Transformation matrix so as to minimize the roundoff noise subject to the l/sub 2/-norm dynamic-range scaling constraints. The proposed method may be regarded as an alternative, but much simpler and more general, approach to Hwang's method for synthesizing the optimal filter structure with minimum roundoff noise. A case study is included to illustrate the utility of the proposed techniques.
H Chung - One of the best experts on this subject based on the ideXlab platform.
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Coordinate Transformation after stereotactic frame reapplication in gamma knife radiosurgery
Physica Medica, 2014Co-Authors: Jeonghoon Park, H Chung, Dong Gyu Kim, Younghoon Kim, Jung Ho Han, Chaeyong KimAbstract:In Gamma Knife radiosurgery, the occurrence of reapplying the stereotactic frame leads to re-examination and re-planning. To avoid undergoing invasive second angiography examination for the treatment of vascular lesions, and reduce re-planning time, a mathematical Coordinate Transformation method using the anatomical information has been developed. The MR or CT images of a human brain before and after frame reapplication were correlated with each other using the Affine Transformation. The Transformation parameters which minimize the RMS error of the original and transformed Coordinates between the images were determined using a genetic algorithm. Three CT image studies of skull phantom and five MR image studies of patients were used for the evaluation. The RMS error in the Coordinate Transformation of skull phantom and clinical images was 0.3 ± 0.1 mm and 0.6 ± 0.1 mm, respectively. The original treatment plans of patients were converted to new plans using the Transformation matrix. For total 9 treatment lesions of 0.2-14.1 cc, 3% and 11% RMS error in the irradiation time and target coverage were found respectively. The deeply-located lesions showed a better RMS error of 3% in the conformity index and similar dose distribution than superficial lesions close to the skull.
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su e t 402 Coordinate Transformation after stereotactic frame reapplication in gamma knife radiosurgery
Medical Physics, 2012Co-Authors: Jeonghoon Park, Jung Ho Han, Chaeyong Kim, Taesuk Suh, Dong Geon Kim, H ChungAbstract:Purpose: In Gamma Knife (GK) radiosurgery, the occurrence of reapplying the stereotactic frame due to collision with the collimator leads to re‐ examination and re‐planning. For the treatment of vascular lesions, it is a burden not only to physicians but also to patients to get invasive angiography procedure again. To avoid undergoing second angiography examination, and reduce re‐planning time, a mathematical Coordinate Transformation method using the stereotactic images has been developed. Methods: The MR or CTimages of a patient brain before and after frame reapplication can be correlated with each other using the Affine Transformation. The Transformation parameters which minimize the RMS error of the original and transformed Coordinates between the images were determined using a genetic algorithm. Three CTimage studies of skull phantom were used for the verification of the algorithm. Moreover, five MR image studies of patients who underwent more than one GK procedure were used for the clinical evaluation. The Coordinates under the original treatment plan were converted to new Coordinates using the Transformation matrix, and their dosimetric outcomes were compared. Results: The RMS error in the Coordinate Transformation of skull phantom and clinical images was 0.3 mm and 0.6 mm, respectively. For total 9 treatment lesions of 0.2 ∼14.1 cc, 3% and 11% RMS error in the irradiation time and target coverage were found respectively. The patients with only translational movement during the frame reapplication showed similar plan conversion results with the original plan. Also, deeply‐located lesions showed a better RMS error of 3% in the conformity index than superficial lesions close to the skull. Conclusions: New treatment plans were obtained by applying the Coordinate Transformation to the original plans after the frame reapplication. The converted plans maintained the quality of the original plans with a little change in dose distribution arising from head rotation. This work was supported by a grant no. 04‐2011‐0320110130 from the Seoul National University Hospital Research Fund and a National Research Foundation of Korea (NRFK) grant funded by the Korean government (MEST) (Grant No. K20901000001‐09E0100‐00110).
Takao Hinamoto - One of the best experts on this subject based on the ideXlab platform.
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separate joint optimization of error feedback and Coordinate Transformation for roundoff noise minimization in two dimensional state space digital filters
IEEE Transactions on Signal Processing, 2003Co-Authors: Takao Hinamoto, K Higashi, Wusheng LuAbstract:This paper is concerned with the minimization of roundoff noise subject to l/sub 2/-norm dynamic-range scaling constraints in two-dimensional (2-D) state-space digital filters. Two methods are proposed, with the first one using error feedback alone and the second one using joint error feedback and Coordinate Transformation optimization. In the first method, several techniques for the determination of optimal full-scale, block-diagonal, diagonal, and scalar error-feedback matrices for a given 2-D state-space digital filter are proposed. In the second method, an iterative approach for minimizing the roundoff noise under l/sub 2/-norm dynamic-range scaling constraints is developed by jointly optimizing a scalar error-feedback matrix and a Coordinate Transformation matrix, which may be regarded as an alternative approach to the conventional method for synthesizing the optimal 2-D filter structure with minimum roundoff noise. An analytical method for the joint optimization of a general error-feedback matrix and a Coordinate Transformation matrix under the scaling constraints is also proposed. A numerical example is presented to illustrate the utility of the proposed techniques.
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joint optimization of error feedback and Coordinate Transformation for roundoff noise minimization in 2d state space digital filters
International Symposium on Circuits and Systems, 2003Co-Authors: Takao Hinamoto, H Ohnishi, Wusheng LuAbstract:An iterative approach for joint optimization of a scalar error-feedback matrix and a Coordinate Transformation matrix is developed to minimize the roundoff noise subject to the l/sub 2/-norm dynamic-range scaling constraints. When the iterative algorithm converges and the optimal Coordinate Transformation matrix is obtained, the diagonal error-feedback matrix is derived to minimize the noise gain in the optimal state-space realization. This diagonal error-feedback matrix enables one to produce more reduction of the noise gain. Finally, a numerical example is given to illustrate the utility of the proposed technique.
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roundoff noise minimization of state space digital filters using separate and joint error feedback Coordinate Transformation optimization
IEEE Transactions on Circuits and Systems I-regular Papers, 2003Co-Authors: Takao Hinamoto, H Ohnishi, Wusheng LuAbstract:This paper investigates the problem of minimizing roundoff noise under l/sub 2/-norm dynamic-range scaling constraints in state-space digital fibers by means of error feedback as well as joint error feedback/Coordinate Transformation optimization. First, several techniques, for the determination of optimal full-scale, diagonal, and scalar error-feedback matrices for a given state-space digital filter are proposed, where three realization schemes, namely, the general state-space realization, input-balanced realization, and optimal realization in the sense of Hwang-Mullis-Roberts are examined. Furthermore, an iterative approach is developed for jointly optimizing a scalar error-feedback matrix and a Coordinate Transformation matrix so as to minimize the roundoff noise subject to the l/sub 2/-norm dynamic-range scaling constraints. The proposed method may be regarded as an alternative, but much simpler and more general, approach to Hwang's method for synthesizing the optimal filter structure with minimum roundoff noise. A case study is included to illustrate the utility of the proposed techniques.
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minimization of roundoff noise in state space digital filters using error feedback and Coordinate Transformation
International Symposium on Circuits and Systems, 2002Co-Authors: Takao Hinamoto, H OhnishiAbstract:A systematic approach is developed to obtain the optimal Coordinate Transformation matrix that minimizes the roundoff noise in state-space digital filters, under the l/sub 2/-norm, dynamic-range constraints. This is an alternative approach to Hwang's method for constructing the optimal realization with minimum roundoff noise, and is much simpler than the conventional method. Next, error feedback is applied to both the optimal realization and the input-balanced realization. Finally, a numerical example is given to illustrate the utility of the proposed technique.
Chaeyong Kim - One of the best experts on this subject based on the ideXlab platform.
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Coordinate Transformation after stereotactic frame reapplication in gamma knife radiosurgery
Physica Medica, 2014Co-Authors: Jeonghoon Park, H Chung, Dong Gyu Kim, Younghoon Kim, Jung Ho Han, Chaeyong KimAbstract:In Gamma Knife radiosurgery, the occurrence of reapplying the stereotactic frame leads to re-examination and re-planning. To avoid undergoing invasive second angiography examination for the treatment of vascular lesions, and reduce re-planning time, a mathematical Coordinate Transformation method using the anatomical information has been developed. The MR or CT images of a human brain before and after frame reapplication were correlated with each other using the Affine Transformation. The Transformation parameters which minimize the RMS error of the original and transformed Coordinates between the images were determined using a genetic algorithm. Three CT image studies of skull phantom and five MR image studies of patients were used for the evaluation. The RMS error in the Coordinate Transformation of skull phantom and clinical images was 0.3 ± 0.1 mm and 0.6 ± 0.1 mm, respectively. The original treatment plans of patients were converted to new plans using the Transformation matrix. For total 9 treatment lesions of 0.2-14.1 cc, 3% and 11% RMS error in the irradiation time and target coverage were found respectively. The deeply-located lesions showed a better RMS error of 3% in the conformity index and similar dose distribution than superficial lesions close to the skull.
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su e t 402 Coordinate Transformation after stereotactic frame reapplication in gamma knife radiosurgery
Medical Physics, 2012Co-Authors: Jeonghoon Park, Jung Ho Han, Chaeyong Kim, Taesuk Suh, Dong Geon Kim, H ChungAbstract:Purpose: In Gamma Knife (GK) radiosurgery, the occurrence of reapplying the stereotactic frame due to collision with the collimator leads to re‐ examination and re‐planning. For the treatment of vascular lesions, it is a burden not only to physicians but also to patients to get invasive angiography procedure again. To avoid undergoing second angiography examination, and reduce re‐planning time, a mathematical Coordinate Transformation method using the stereotactic images has been developed. Methods: The MR or CTimages of a patient brain before and after frame reapplication can be correlated with each other using the Affine Transformation. The Transformation parameters which minimize the RMS error of the original and transformed Coordinates between the images were determined using a genetic algorithm. Three CTimage studies of skull phantom were used for the verification of the algorithm. Moreover, five MR image studies of patients who underwent more than one GK procedure were used for the clinical evaluation. The Coordinates under the original treatment plan were converted to new Coordinates using the Transformation matrix, and their dosimetric outcomes were compared. Results: The RMS error in the Coordinate Transformation of skull phantom and clinical images was 0.3 mm and 0.6 mm, respectively. For total 9 treatment lesions of 0.2 ∼14.1 cc, 3% and 11% RMS error in the irradiation time and target coverage were found respectively. The patients with only translational movement during the frame reapplication showed similar plan conversion results with the original plan. Also, deeply‐located lesions showed a better RMS error of 3% in the conformity index than superficial lesions close to the skull. Conclusions: New treatment plans were obtained by applying the Coordinate Transformation to the original plans after the frame reapplication. The converted plans maintained the quality of the original plans with a little change in dose distribution arising from head rotation. This work was supported by a grant no. 04‐2011‐0320110130 from the Seoul National University Hospital Research Fund and a National Research Foundation of Korea (NRFK) grant funded by the Korean government (MEST) (Grant No. K20901000001‐09E0100‐00110).
Jung Ho Han - One of the best experts on this subject based on the ideXlab platform.
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Coordinate Transformation after stereotactic frame reapplication in gamma knife radiosurgery
Physica Medica, 2014Co-Authors: Jeonghoon Park, H Chung, Dong Gyu Kim, Younghoon Kim, Jung Ho Han, Chaeyong KimAbstract:In Gamma Knife radiosurgery, the occurrence of reapplying the stereotactic frame leads to re-examination and re-planning. To avoid undergoing invasive second angiography examination for the treatment of vascular lesions, and reduce re-planning time, a mathematical Coordinate Transformation method using the anatomical information has been developed. The MR or CT images of a human brain before and after frame reapplication were correlated with each other using the Affine Transformation. The Transformation parameters which minimize the RMS error of the original and transformed Coordinates between the images were determined using a genetic algorithm. Three CT image studies of skull phantom and five MR image studies of patients were used for the evaluation. The RMS error in the Coordinate Transformation of skull phantom and clinical images was 0.3 ± 0.1 mm and 0.6 ± 0.1 mm, respectively. The original treatment plans of patients were converted to new plans using the Transformation matrix. For total 9 treatment lesions of 0.2-14.1 cc, 3% and 11% RMS error in the irradiation time and target coverage were found respectively. The deeply-located lesions showed a better RMS error of 3% in the conformity index and similar dose distribution than superficial lesions close to the skull.
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su e t 402 Coordinate Transformation after stereotactic frame reapplication in gamma knife radiosurgery
Medical Physics, 2012Co-Authors: Jeonghoon Park, Jung Ho Han, Chaeyong Kim, Taesuk Suh, Dong Geon Kim, H ChungAbstract:Purpose: In Gamma Knife (GK) radiosurgery, the occurrence of reapplying the stereotactic frame due to collision with the collimator leads to re‐ examination and re‐planning. For the treatment of vascular lesions, it is a burden not only to physicians but also to patients to get invasive angiography procedure again. To avoid undergoing second angiography examination, and reduce re‐planning time, a mathematical Coordinate Transformation method using the stereotactic images has been developed. Methods: The MR or CTimages of a patient brain before and after frame reapplication can be correlated with each other using the Affine Transformation. The Transformation parameters which minimize the RMS error of the original and transformed Coordinates between the images were determined using a genetic algorithm. Three CTimage studies of skull phantom were used for the verification of the algorithm. Moreover, five MR image studies of patients who underwent more than one GK procedure were used for the clinical evaluation. The Coordinates under the original treatment plan were converted to new Coordinates using the Transformation matrix, and their dosimetric outcomes were compared. Results: The RMS error in the Coordinate Transformation of skull phantom and clinical images was 0.3 mm and 0.6 mm, respectively. For total 9 treatment lesions of 0.2 ∼14.1 cc, 3% and 11% RMS error in the irradiation time and target coverage were found respectively. The patients with only translational movement during the frame reapplication showed similar plan conversion results with the original plan. Also, deeply‐located lesions showed a better RMS error of 3% in the conformity index than superficial lesions close to the skull. Conclusions: New treatment plans were obtained by applying the Coordinate Transformation to the original plans after the frame reapplication. The converted plans maintained the quality of the original plans with a little change in dose distribution arising from head rotation. This work was supported by a grant no. 04‐2011‐0320110130 from the Seoul National University Hospital Research Fund and a National Research Foundation of Korea (NRFK) grant funded by the Korean government (MEST) (Grant No. K20901000001‐09E0100‐00110).
