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You searched for +publisher:"Delft University of Technology" +contributor:("Breedveld, S."). Showing records 1 – 3 of 3 total matches.

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Delft University of Technology

1. Ruckstuhl, Y.M. (author). Investigation of Different Solvers for Radiotherapy Treatment Planning Problems.

Degree: 2014, Delft University of Technology

Radiotherapy treatment planning involves solving inequality constrained minimization problems. The currently used interior point solver performs well, but is considered relatively slow. In this thesis we investigate two different solvers based on the logarithmic barrier method and Sequential Quadratic Programming (SQP) respectively. We argue that the behaviour of the logarithmic barrier solver is uncertain, thereby making it generally unreliable in this context. In addition we substantiate that the performance of the SQP solver is solid, but lacks efficiency in computing the minimizers of its related quadratic subproblems. We conclude that without serious improvements, none of the solvers investigated are faster than the currently used interior point optimizer.

Applied mathematics

Electrical Engineering, Mathematics and Computer Science

Advisors/Committee Members: Keijzer, M. (mentor), Breedveld, S. (mentor).

Subjects/Keywords: barrier method

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ruckstuhl, Y. M. (. (2014). Investigation of Different Solvers for Radiotherapy Treatment Planning Problems. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:13d72d18-cee1-4b32-8a97-36301c6b5bcd

Chicago Manual of Style (16th Edition):

Ruckstuhl, Y M (author). “Investigation of Different Solvers for Radiotherapy Treatment Planning Problems.” 2014. Masters Thesis, Delft University of Technology. Accessed April 20, 2021. http://resolver.tudelft.nl/uuid:13d72d18-cee1-4b32-8a97-36301c6b5bcd.

MLA Handbook (7th Edition):

Ruckstuhl, Y M (author). “Investigation of Different Solvers for Radiotherapy Treatment Planning Problems.” 2014. Web. 20 Apr 2021.

Vancouver:

Ruckstuhl YM(. Investigation of Different Solvers for Radiotherapy Treatment Planning Problems. [Internet] [Masters thesis]. Delft University of Technology; 2014. [cited 2021 Apr 20]. Available from: http://resolver.tudelft.nl/uuid:13d72d18-cee1-4b32-8a97-36301c6b5bcd.

Council of Science Editors:

Ruckstuhl YM(. Investigation of Different Solvers for Radiotherapy Treatment Planning Problems. [Masters Thesis]. Delft University of Technology; 2014. Available from: http://resolver.tudelft.nl/uuid:13d72d18-cee1-4b32-8a97-36301c6b5bcd


Delft University of Technology

2. Van Haveren, R. (author). Lexicographic Reference Point Method for Automatic Treatment Planning in Radiation Therapy.

Degree: 2014, Delft University of Technology

Treatment plan generation in radiation therapy is a multicriteria optimization problem, in which multiple, often conflicting, criteria need to be optimized simultaneously. Several methods can be used to obtain Pareto optimal treatment plans, meaning that no criterion can be improved without deteriorating another criterion. The focus is on the 2-phase ?-constraint (2p?c) method and the reference point method (RPM), which both automatically generate Pareto optimal intensity modulated radiation therapy (IMRT) plans. Although the plans of the 2p?c method are of high quality, several optimizations need to be performed. For the RPM, only a single optimization is needed per plan. The aim of this thesis is configure the RPM so that the resulting treatment plans are of the same quality as the treatment plans generated by the 2p?c method, and thereby reducing the computation time. The 2p?c method prioritizes the criteria and assigns goal values to them. Then, each criterion is iteratively optimized and constrained according to a rule (depending on whether the goal value was met or not). The number of optimizations needed scales linearly with the number of criteria. A specific configuration of the RPM, namely the lexicographic reference point method (LRPM), maintains the lexicographic ordering of the criteria. Both the 2p?c method and the LRPM have been tested on 30 prostate cancer patients and 2 head-and-neck cancer patients. For the 30 prostate cancer patients, all treatment plans generated by the LRPM were found of similar quality when compared to the plans generated by the 2p?c method. On average, the computation time of the LRPM was 3 minutes, which is a speed-up factor of nearly 12. For the 2 head-and-neck cancer patients, the plans of the LRPM were considered as good as or better than the plans of the 2p?c method with a speed-up factor for the computation time of 3-4.

Applied mathematics

Electrical Engineering, Mathematics and Computer Science

Advisors/Committee Members: Keijzer, M. (mentor), Breedveld, S. (mentor).

Subjects/Keywords: multicriteria optimization; lexicographic reference point method; radiation therapy; treatment planning; fluence map optimization

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APA (6th Edition):

Van Haveren, R. (. (2014). Lexicographic Reference Point Method for Automatic Treatment Planning in Radiation Therapy. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:29a7d929-fcfc-408a-9c91-e4c8007f53d6

Chicago Manual of Style (16th Edition):

Van Haveren, R (author). “Lexicographic Reference Point Method for Automatic Treatment Planning in Radiation Therapy.” 2014. Masters Thesis, Delft University of Technology. Accessed April 20, 2021. http://resolver.tudelft.nl/uuid:29a7d929-fcfc-408a-9c91-e4c8007f53d6.

MLA Handbook (7th Edition):

Van Haveren, R (author). “Lexicographic Reference Point Method for Automatic Treatment Planning in Radiation Therapy.” 2014. Web. 20 Apr 2021.

Vancouver:

Van Haveren R(. Lexicographic Reference Point Method for Automatic Treatment Planning in Radiation Therapy. [Internet] [Masters thesis]. Delft University of Technology; 2014. [cited 2021 Apr 20]. Available from: http://resolver.tudelft.nl/uuid:29a7d929-fcfc-408a-9c91-e4c8007f53d6.

Council of Science Editors:

Van Haveren R(. Lexicographic Reference Point Method for Automatic Treatment Planning in Radiation Therapy. [Masters Thesis]. Delft University of Technology; 2014. Available from: http://resolver.tudelft.nl/uuid:29a7d929-fcfc-408a-9c91-e4c8007f53d6


Delft University of Technology

3. Bennan, Amit (author). Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer.

Degree: 2017, Delft University of Technology

Introduction: High Dose Rate (HDR) Brachytherapy is a radiotherapy modality that involves temporarily introducing a highly radioactive source into the target volume with the use of an applicator. With respect to HDR brachytherapy for prostate cancer, an 192Iridium source is driven into the target volume through catheters implanted into the prostate. The dose delivered to a point in the prostate depends on the time the source dwells at a given position. Treatment planning for brachytherapy involve the optimization of dwell times and dwell positions. The aim of the treatment plan is to deliver the prescribed dose to the target volume, the prostate, while minimizing the dose to the organs at risk (OAR), namely the urethra, bladder and rectum. In current clinical practice, the process of treatment planning involves the manual manipulation of the parameters of an optimizer until the desired dose distribution is achieved. This implies that the plan quality depends on the experience of the planner, and there is variation in plan quality between planners. The aim of this project was to develop an automated treatment planning system that would able to generate clinically acceptable plans with minimal human intervention. The brachytherapy treatment planning module is named B-iCycle and may be integrated in the future with the treatment planning software suite, called Erasmus-iCycle, developed at the Erasmus MC. Materials and methods: At the core of the treatment planning system (TPS) is a precise and fast dose engine that is able to simulate the dose to be delivered. In this project, we employ the TG-43 dose calculation formalism as it is the most widely implemented method in dose engines for brachytherapy treatment planning systems. The dose engine is then verified against the dose engine of the clinical treatment planning system. B-iCycle uses the 2-phase ϵ-constraint (2pϵc) algorithm to optimize the dwell times and positions. The 2pϵc algorithm requires a ‘wish-list’, which encapsulates the treatment protocol as goals and constraints for each critical structure. For this project three treatment protocols were chosen, four fractions of 9.5 Gy, single fraction of 19 Gy and single fraction of 20 Gy, and wish-lists were generated for each protocol. Three patient groups with different catheter geometries were selected. Treatment plans were generated for each patient and compared against the plans that were generated, for the same patients, in the clinic. The treatment plans that were generated in B-iCycle were then exported to the clinical treatment planning system (Oncentra from Elekta) to obtain the dose characteristics. The plans were compared based on the dose characteristics and the Conformity Index (COIN). The plans were also verified by a radiation oncologist. Results: The TG-43 dose engine was successfully verified against the clinical dose engine. The Gamma analysis showed that only 0.68% of the voxels failed the gamma analysis and these voxels were located within the catheters therefore they can be ignored as… Advisors/Committee Members: Schaart, Dennis (mentor), Breedveld, S. (mentor), Kolkman-Deurloo, I.K.K. (mentor), Heijman, B.J.M. (mentor), Lathouwers, Danny (mentor), Goorden, Marlies (mentor), Delft University of Technology (degree granting institution).

Subjects/Keywords: brachytherapy; Treatment Planning; prostate cancer; HDR

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bennan, A. (. (2017). Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2c0ade14-fc3a-413d-bebc-a6f9ff71fb25

Chicago Manual of Style (16th Edition):

Bennan, Amit (author). “Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer.” 2017. Masters Thesis, Delft University of Technology. Accessed April 20, 2021. http://resolver.tudelft.nl/uuid:2c0ade14-fc3a-413d-bebc-a6f9ff71fb25.

MLA Handbook (7th Edition):

Bennan, Amit (author). “Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer.” 2017. Web. 20 Apr 2021.

Vancouver:

Bennan A(. Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Apr 20]. Available from: http://resolver.tudelft.nl/uuid:2c0ade14-fc3a-413d-bebc-a6f9ff71fb25.

Council of Science Editors:

Bennan A(. Automated Treatment Planning in HDR Brachytherapy for Prostate Cancer. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:2c0ade14-fc3a-413d-bebc-a6f9ff71fb25

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