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公开(公告)号:US20200075151A1
公开(公告)日:2020-03-05
申请号:US16558698
申请日:2019-09-03
Inventor: Troy Long , Mingli Chen , Steve Jiang , Weiguo Lu
Abstract: A method and system for generating a voxel-based quadratic penalty model for automatic intensity modulated radiation therapy (IMRT) treatment planning are disclosed herein. A computing system generates an initial assignment of threshold values to a penalty function for IMRT treatment planning The computing system receives an update to a dose value associated with the IMRT treatment planning The computing system dynamically updates the threshold values based on the updated dose value. The computing system continues to iterate the threshold values based on further updated dose values.
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公开(公告)号:US10660587B2
公开(公告)日:2020-05-26
申请号:US16443419
申请日:2019-06-17
Inventor: Hak Choy , Steve Jiang , Robert Timmerman , Arnold Pompos
Abstract: Radiation therapy systems and their components, including secondary radiation shields. At least some versions of the disclosed systems combine a radiation delivery device, a primary radiation shielding device, and a secondary shielding layer into an integrated, modular unit. This is accomplished by using a small direct beam shield capable of blocking a primary beam from a radiation delivery device. In turn, a thinner shielding layer can be used to surround the radiation delivery device and primary shielding device, enabling a single modular unit to be delivered to an installation site. In some embodiments, a bed may be disposed within the secondary shielding layer. In some embodiments, the system is configured to provide up to 4-pi (4π) steradians of radiation coverage to the bed from the radiation delivery device.
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3.
公开(公告)号:US20190365337A1
公开(公告)日:2019-12-05
申请号:US16443419
申请日:2019-06-17
Inventor: Hak Choy , Steve Jiang , Robert Timmerman , Arnold Pompos
Abstract: Radiation therapy systems and their components, including secondary radiation shields. At least some versions of the disclosed systems combine a radiation delivery device, a primary radiation shielding device, and a secondary shielding layer into an integrated, modular unit. This is accomplished by using a small direct beam shield capable of blocking a primary beam from a radiation delivery device. In turn, a thinner shielding layer can be used to surround the radiation delivery device and primary shielding device, enabling a single modular unit to be delivered to an installation site. In some embodiments, a bed may be disposed within the secondary shielding layer. In some embodiments, the system is configured to provide up to 4-pi (4π) steradians of radiation coverage to the bed from the radiation delivery device.
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公开(公告)号:US11865362B2
公开(公告)日:2024-01-09
申请号:US16863147
申请日:2020-04-30
Inventor: Dan Nguyen , Azar Sadeghnejad Barkousaraie , Steve Jiang
CPC classification number: A61N5/1031 , A61N5/1036 , A61N5/1039 , A61N5/1045 , G16H20/40 , G16H30/20 , A61N2005/1034
Abstract: A method for determining a radiotherapy treatment plan can include: receiving anatomical data for a patient; generating, via a neural network analyzing the anatomical data, a plurality of fitness values for a plurality of candidate beam orientations; determining a selected beam orientation based on the plurality of fitness values; performing a fluence map optimization (FMO) process on the selected beam orientation; and determining a dose distribution for the patient based on the FMO process.
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公开(公告)号:US11651847B2
公开(公告)日:2023-05-16
申请号:US16558698
申请日:2019-09-03
Inventor: Troy Long , Mingli Chen , Steve Jiang , Weiguo Lu
CPC classification number: G16H20/40 , A61N5/1031
Abstract: A method and system for generating a voxel-based quadratic penalty model for automatic intensity modulated radiation therapy (IMRT) treatment planning are disclosed herein. A computing system generates an initial assignment of threshold values to a penalty function for IMRT treatment planning. The computing system receives an update to a dose value associated with the IMRT treatment planning. The computing system dynamically updates the threshold values based on the updated dose value. The computing system continues to iterate the threshold values based on further updated dose values.
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公开(公告)号:US10660586B2
公开(公告)日:2020-05-26
申请号:US16443360
申请日:2019-06-17
Inventor: Hak Choy , Steve Jiang , Robert Timmerman , Arnold Pompos
Abstract: Radiation therapy systems and their components, including secondary radiation shields. At least some versions of the disclosed systems combine a radiation delivery device, a primary radiation shielding device, and a secondary shielding layer into an integrated, modular unit. This is accomplished by using a small direct beam shield capable of blocking a primary beam from a radiation delivery device. In turn, a thinner shielding layer can be used to surround the radiation delivery device and primary shielding device, enabling a single modular unit to be delivered to an installation site. In some embodiments, a bed may be disposed within the secondary shielding layer. In some embodiments, the system is configured to provide up to 4-pi (4π) steradians of radiation coverage to the bed from the radiation delivery device.
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公开(公告)号:US20210339048A1
公开(公告)日:2021-11-04
申请号:US16863147
申请日:2020-04-30
Inventor: Dan Nguyen , Azar Sadeghnejad Barkousaraie , Steve Jiang
Abstract: A method for determining a radiotherapy treatment plan can include: receiving anatomical data for a patient; generating, via a neural network analyzing the anatomical data, a plurality of fitness values for a plurality of candidate beam orientations; determining a selected beam orientation based on the plurality of fitness values; performing a fluence map optimization (FMO) process on the selected beam orientation; and determining a dose distribution for the patient based on the FMO process.
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8.
公开(公告)号:US20190307406A1
公开(公告)日:2019-10-10
申请号:US16443360
申请日:2019-06-17
Inventor: Hak CHOY , Steve Jiang , Robert Timmerman , Arnold Pompos
Abstract: Radiation therapy systems and their components, including secondary radiation shields. At least some versions of the disclosed systems combine a radiation delivery device, a primary radiation shielding device, and a secondary shielding layer into an integrated, modular unit. This is accomplished by using a small direct beam shield capable of blocking a primary beam from a radiation delivery device. In turn, a thinner shielding layer can be used to surround the radiation delivery device and primary shielding device, enabling a single modular unit to be delivered to an installation site. In some embodiments, a bed may be disposed within the secondary shielding layer. In some embodiments, the system is configured to provide up to 4-pi (4π) steradians of radiation coverage to the bed from the radiation delivery device.
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公开(公告)号:US11615873B2
公开(公告)日:2023-03-28
申请号:US16558681
申请日:2019-09-03
Inventor: Dan Nguyen , Steve Jiang
Abstract: A method and system for generating a treatment plan are disclosed herein. A computing system receives a plurality of dose volume histograms for a plurality of patients and a plurality of volumetric dose distributions corresponding to the plurality of dose volume histograms. The computing system generates a volumetric dose prediction model using a neural network by learning, by the neural network, a relationship between a plurality of dose volume histograms for the plurality of patients and the corresponding plurality of volumetric dose distributions. The computing system receives a candidate dose volume histogram for a target patient. The computing system infers, via the volumetric dose prediction module, a volumetric dose prediction distribution matching the candidate dose volume histogram. The computing system generates a recommendation based on the inferred volumetric dose prediction distribution.
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10.
公开(公告)号:US20200075148A1
公开(公告)日:2020-03-05
申请号:US16558681
申请日:2019-09-03
Inventor: Dan Nguyen , Steve Jiang
Abstract: A method and system for generating a treatment plan are disclosed herein. A computing system receives a plurality of dose volume histograms for a plurality of patients and a plurality of volumetric dose distributions corresponding to the plurality of dose volume histograms. The computing system generates a volumetric dose prediction model using a neural network by learning, by the neural network, a relationship between a plurality of dose volume histograms for the plurality of patients and the corresponding plurality of volumetric dose distributions. The computing system receives a candidate dose volume histogram for a target patient. The computing system infers, via the volumetric dose prediction module, a volumetric dose prediction distribution matching the candidate dose volume histogram. The computing system generates a recommendation based on the inferred volumetric dose prediction distribution.
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