The Experts below are selected from a list of 16884 Experts worldwide ranked by ideXlab platform
R Boostani - One of the best experts on this subject based on the ideXlab platform.
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su e t 614 an optimization algorithm for beam angle beam weight and wedge angle in forward treatment planning of external beam radiotherapy based on an integer representation adaptive Mutation Probability genetic algorithm
Medical Physics, 2011Co-Authors: H Mahani, Mohammad Amin Moslehshirazi, Reza Faghihi, K Hadad, R BoostaniAbstract:Purpose: To present the development of an optimization algorithm for beam angle, beam weight and wedge angle in forward treatment planning of external‐beam radiotherapy using a genetic algorithm (GA). Methods: An adaptive Mutation Probability (AMP) integer‐representation GA was applied for this optimization process in the MATLAB programming environment. The code allows various user‐defined limits and starting points as well as comprehensive searches. We used an integer representation for all variables in the chromosomes pool for encoding the steps, because wedge angles often take discrete values (i.e. 0, 15, 30, 45 and 60 degrees). To improve performance, we designed a dynamic Mutation Probability assignment code in each generation so that the algorithm automatically adapts the Mutation Probability using the standard deviation of fitness values of the population at each generation. If the fitness diversity is great enough, a low Mutation Probability will be applied, and if the fitness values have low diversity, a high Mutation Probability will be applied. A dose calculation program using correction‐based techniques and the CTimages of the patient was also written within the same software. The GA code was tested using a standard test function both with AMP and with a constant Mutation Probability across all GA generations. Convergence of beam angle, beam weight and wedge angle was also investigated. Results: With the AMP technique, the GA maintained the population diversity in the chromosomes pool to avoid premature convergence into a local minimum. Test results showed that the algorithm with AMP (run time of 5 min for a simple standard test function) is more robust compared to the conventional method. Conclusions: This algorithm is a feasible and promising tool for optimization of treatment planning parameters with an acceptable computation time. Testing the algorithm against experienced treatment planners will be performed next.
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SU‐E‐T‐614: An Optimization Algorithm for Beam Angle, Beam Weight and Wedge Angle in Forward Treatment Planning of External‐Beam Radiotherapy Based on an Integer‐Representation Adaptive Mutation Probability Genetic Algorithm
Medical Physics, 2011Co-Authors: H Mahani, Reza Faghihi, K Hadad, Mohammad Amin Mosleh-shirazi, R BoostaniAbstract:Purpose: To present the development of an optimization algorithm for beam angle, beam weight and wedge angle in forward treatment planning of external‐beam radiotherapy using a genetic algorithm (GA). Methods: An adaptive Mutation Probability (AMP) integer‐representation GA was applied for this optimization process in the MATLAB programming environment. The code allows various user‐defined limits and starting points as well as comprehensive searches. We used an integer representation for all variables in the chromosomes pool for encoding the steps, because wedge angles often take discrete values (i.e. 0, 15, 30, 45 and 60 degrees). To improve performance, we designed a dynamic Mutation Probability assignment code in each generation so that the algorithm automatically adapts the Mutation Probability using the standard deviation of fitness values of the population at each generation. If the fitness diversity is great enough, a low Mutation Probability will be applied, and if the fitness values have low diversity, a high Mutation Probability will be applied. A dose calculation program using correction‐based techniques and the CTimages of the patient was also written within the same software. The GA code was tested using a standard test function both with AMP and with a constant Mutation Probability across all GA generations. Convergence of beam angle, beam weight and wedge angle was also investigated. Results: With the AMP technique, the GA maintained the population diversity in the chromosomes pool to avoid premature convergence into a local minimum. Test results showed that the algorithm with AMP (run time of 5 min for a simple standard test function) is more robust compared to the conventional method. Conclusions: This algorithm is a feasible and promising tool for optimization of treatment planning parameters with an acceptable computation time. Testing the algorithm against experienced treatment planners will be performed next.
Maurice P. Zeegers - One of the best experts on this subject based on the ideXlab platform.
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efficiency of brcapro and myriad ii Mutation Probability thresholds versus cancer history criteria alone for brca1 2 Mutation detection
Familial Cancer, 2010Co-Authors: J. J. T. Van Harssel, C. E. P. Van Roozendaal, Y. Detisch, Rita D. Brandão, Aimee D.c. Paulussen, Maurice P. Zeegers, Marinus J. Blok, E Gomez B GarciaAbstract:Considerable differences exist amongst countries in the Mutation Probability methods and thresholds used to select patients for BRCA1/2 genetic screening. In order to assess the added value of Mutation Probability methods, we have retrospectively calculated the BRCAPRO and Myriad II probabilities in 306 probands who had previously been selected for DNA-analysis according to criteria based on familial history of cancer. DNA-analysis identified 52 Mutations (16.9%) and 11 unclassified variants (UVs, 3.6%). Compared to cancer history, a threshold ≥10% with BRCAPRO or with Myriad II excluded about 40% of the patients from analysis, including four with a Mutation and probabilities 20% with BRCAPRO and Myriad II. In summary, BRCAPRO and Myriad II are more efficient than cancer history alone to exclude patients without a Mutation. BRCAPRO performs better for the detection of BRCA1 Mutations than of BRCA2 Mutations. The Myriad II scores provided no additional information than the BRCAPRO scores alone for the detection of patients with a Mutation. The use of thresholds excluded from analysis the majority of patients carrying an UV.
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Efficiency of BRCAPRO and Myriad II Mutation Probability thresholds versus cancer history criteria alone for BRCA1/2 Mutation detection
Familial cancer, 2009Co-Authors: J. J. T. Van Harssel, C. E. P. Van Roozendaal, Y. Detisch, Rita D. Brandão, Aimee D.c. Paulussen, Maurice P. Zeegers, Marinus J. Blok, E. B. Gomez GarciaAbstract:Considerable differences exist amongst countries in the Mutation Probability methods and thresholds used to select patients for BRCA1/2 genetic screening. In order to assess the added value of Mutation Probability methods, we have retrospectively calculated the BRCAPRO and Myriad II probabilities in 306 probands who had previously been selected for DNA-analysis according to criteria based on familial history of cancer. DNA-analysis identified 52 Mutations (16.9%) and 11 unclassified variants (UVs, 3.6%). Compared to cancer history, a threshold ≥10% with BRCAPRO or with Myriad II excluded about 40% of the patients from analysis, including four with a Mutation and probabilities 20% with BRCAPRO and Myriad II. In summary, BRCAPRO and Myriad II are more efficient than cancer history alone to exclude patients without a Mutation. BRCAPRO performs better for the detection of BRCA1 Mutations than of BRCA2 Mutations. The Myriad II scores provided no additional information than the BRCAPRO scores alone for the detection of patients with a Mutation. The use of thresholds excluded from analysis the majority of patients carrying an UV.
J. J. T. Van Harssel - One of the best experts on this subject based on the ideXlab platform.
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efficiency of brcapro and myriad ii Mutation Probability thresholds versus cancer history criteria alone for brca1 2 Mutation detection
Familial Cancer, 2010Co-Authors: J. J. T. Van Harssel, C. E. P. Van Roozendaal, Y. Detisch, Rita D. Brandão, Aimee D.c. Paulussen, Maurice P. Zeegers, Marinus J. Blok, E Gomez B GarciaAbstract:Considerable differences exist amongst countries in the Mutation Probability methods and thresholds used to select patients for BRCA1/2 genetic screening. In order to assess the added value of Mutation Probability methods, we have retrospectively calculated the BRCAPRO and Myriad II probabilities in 306 probands who had previously been selected for DNA-analysis according to criteria based on familial history of cancer. DNA-analysis identified 52 Mutations (16.9%) and 11 unclassified variants (UVs, 3.6%). Compared to cancer history, a threshold ≥10% with BRCAPRO or with Myriad II excluded about 40% of the patients from analysis, including four with a Mutation and probabilities 20% with BRCAPRO and Myriad II. In summary, BRCAPRO and Myriad II are more efficient than cancer history alone to exclude patients without a Mutation. BRCAPRO performs better for the detection of BRCA1 Mutations than of BRCA2 Mutations. The Myriad II scores provided no additional information than the BRCAPRO scores alone for the detection of patients with a Mutation. The use of thresholds excluded from analysis the majority of patients carrying an UV.
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Efficiency of BRCAPRO and Myriad II Mutation Probability thresholds versus cancer history criteria alone for BRCA1/2 Mutation detection
Familial cancer, 2009Co-Authors: J. J. T. Van Harssel, C. E. P. Van Roozendaal, Y. Detisch, Rita D. Brandão, Aimee D.c. Paulussen, Maurice P. Zeegers, Marinus J. Blok, E. B. Gomez GarciaAbstract:Considerable differences exist amongst countries in the Mutation Probability methods and thresholds used to select patients for BRCA1/2 genetic screening. In order to assess the added value of Mutation Probability methods, we have retrospectively calculated the BRCAPRO and Myriad II probabilities in 306 probands who had previously been selected for DNA-analysis according to criteria based on familial history of cancer. DNA-analysis identified 52 Mutations (16.9%) and 11 unclassified variants (UVs, 3.6%). Compared to cancer history, a threshold ≥10% with BRCAPRO or with Myriad II excluded about 40% of the patients from analysis, including four with a Mutation and probabilities 20% with BRCAPRO and Myriad II. In summary, BRCAPRO and Myriad II are more efficient than cancer history alone to exclude patients without a Mutation. BRCAPRO performs better for the detection of BRCA1 Mutations than of BRCA2 Mutations. The Myriad II scores provided no additional information than the BRCAPRO scores alone for the detection of patients with a Mutation. The use of thresholds excluded from analysis the majority of patients carrying an UV.
H Mahani - One of the best experts on this subject based on the ideXlab platform.
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su e t 614 an optimization algorithm for beam angle beam weight and wedge angle in forward treatment planning of external beam radiotherapy based on an integer representation adaptive Mutation Probability genetic algorithm
Medical Physics, 2011Co-Authors: H Mahani, Mohammad Amin Moslehshirazi, Reza Faghihi, K Hadad, R BoostaniAbstract:Purpose: To present the development of an optimization algorithm for beam angle, beam weight and wedge angle in forward treatment planning of external‐beam radiotherapy using a genetic algorithm (GA). Methods: An adaptive Mutation Probability (AMP) integer‐representation GA was applied for this optimization process in the MATLAB programming environment. The code allows various user‐defined limits and starting points as well as comprehensive searches. We used an integer representation for all variables in the chromosomes pool for encoding the steps, because wedge angles often take discrete values (i.e. 0, 15, 30, 45 and 60 degrees). To improve performance, we designed a dynamic Mutation Probability assignment code in each generation so that the algorithm automatically adapts the Mutation Probability using the standard deviation of fitness values of the population at each generation. If the fitness diversity is great enough, a low Mutation Probability will be applied, and if the fitness values have low diversity, a high Mutation Probability will be applied. A dose calculation program using correction‐based techniques and the CTimages of the patient was also written within the same software. The GA code was tested using a standard test function both with AMP and with a constant Mutation Probability across all GA generations. Convergence of beam angle, beam weight and wedge angle was also investigated. Results: With the AMP technique, the GA maintained the population diversity in the chromosomes pool to avoid premature convergence into a local minimum. Test results showed that the algorithm with AMP (run time of 5 min for a simple standard test function) is more robust compared to the conventional method. Conclusions: This algorithm is a feasible and promising tool for optimization of treatment planning parameters with an acceptable computation time. Testing the algorithm against experienced treatment planners will be performed next.
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SU‐E‐T‐614: An Optimization Algorithm for Beam Angle, Beam Weight and Wedge Angle in Forward Treatment Planning of External‐Beam Radiotherapy Based on an Integer‐Representation Adaptive Mutation Probability Genetic Algorithm
Medical Physics, 2011Co-Authors: H Mahani, Reza Faghihi, K Hadad, Mohammad Amin Mosleh-shirazi, R BoostaniAbstract:Purpose: To present the development of an optimization algorithm for beam angle, beam weight and wedge angle in forward treatment planning of external‐beam radiotherapy using a genetic algorithm (GA). Methods: An adaptive Mutation Probability (AMP) integer‐representation GA was applied for this optimization process in the MATLAB programming environment. The code allows various user‐defined limits and starting points as well as comprehensive searches. We used an integer representation for all variables in the chromosomes pool for encoding the steps, because wedge angles often take discrete values (i.e. 0, 15, 30, 45 and 60 degrees). To improve performance, we designed a dynamic Mutation Probability assignment code in each generation so that the algorithm automatically adapts the Mutation Probability using the standard deviation of fitness values of the population at each generation. If the fitness diversity is great enough, a low Mutation Probability will be applied, and if the fitness values have low diversity, a high Mutation Probability will be applied. A dose calculation program using correction‐based techniques and the CTimages of the patient was also written within the same software. The GA code was tested using a standard test function both with AMP and with a constant Mutation Probability across all GA generations. Convergence of beam angle, beam weight and wedge angle was also investigated. Results: With the AMP technique, the GA maintained the population diversity in the chromosomes pool to avoid premature convergence into a local minimum. Test results showed that the algorithm with AMP (run time of 5 min for a simple standard test function) is more robust compared to the conventional method. Conclusions: This algorithm is a feasible and promising tool for optimization of treatment planning parameters with an acceptable computation time. Testing the algorithm against experienced treatment planners will be performed next.
E Gomez B Garcia - One of the best experts on this subject based on the ideXlab platform.
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efficiency of brcapro and myriad ii Mutation Probability thresholds versus cancer history criteria alone for brca1 2 Mutation detection
Familial Cancer, 2010Co-Authors: J. J. T. Van Harssel, C. E. P. Van Roozendaal, Y. Detisch, Rita D. Brandão, Aimee D.c. Paulussen, Maurice P. Zeegers, Marinus J. Blok, E Gomez B GarciaAbstract:Considerable differences exist amongst countries in the Mutation Probability methods and thresholds used to select patients for BRCA1/2 genetic screening. In order to assess the added value of Mutation Probability methods, we have retrospectively calculated the BRCAPRO and Myriad II probabilities in 306 probands who had previously been selected for DNA-analysis according to criteria based on familial history of cancer. DNA-analysis identified 52 Mutations (16.9%) and 11 unclassified variants (UVs, 3.6%). Compared to cancer history, a threshold ≥10% with BRCAPRO or with Myriad II excluded about 40% of the patients from analysis, including four with a Mutation and probabilities 20% with BRCAPRO and Myriad II. In summary, BRCAPRO and Myriad II are more efficient than cancer history alone to exclude patients without a Mutation. BRCAPRO performs better for the detection of BRCA1 Mutations than of BRCA2 Mutations. The Myriad II scores provided no additional information than the BRCAPRO scores alone for the detection of patients with a Mutation. The use of thresholds excluded from analysis the majority of patients carrying an UV.
