Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/487681
Title: design of an optimal controller using optimization techniques
Researcher: Singh Pushpendra
Guide(s): Tripathi Supriya
Keywords: 
University: Chhattisgarh Swami Vivekanand Technical University
Completed Date: 2023
Abstract: newline Cancer in one of the deadliest disease today, and with a fast-growing aging society, it poses a significant current and future concern. Fortunately, developments in technology and science are consistenly contributing to a deduction in cancer mortifity and treatment adverse effects. The Prime objective of this work is to contribute to these advancements by achieving an optimal reduction in the growth of the tumor cells with minimum side effects, thereby improving the prospects of future cancer patients survival and well-being. newline newlineThe thesis focuses on the advancement of radiation therapy, which is used is both curative and palliative cancer treatments. Lonizing is used to target malignant cells in the body during radiation therapy. Radiation damages cancerous cells DNA, preventing them from proliferating further. Radiation, on the other hand, is detrimental to healthy cells, so it is essential that the patients s irradiation be conducted in such a manner that the ceitical oragans in the proximity of the tumor are protected from radiation. newline newlineThe opposing goals of enchacing tumor control and reducing the consequences for normal tissue are at the heart of all cancer therepy procedures. As a result, many components of the cancer therapy planning process may be formulated as optimization problems, leading to the formation of mathematically sound treatment planning algorithms. newline newlineIn the dissertation, we provide three unique optimization approaches to solve the challenges in cancer treatment olanning: 1) Fluence map optimization for inverse treatment planning, which is well suited to dealing with nonconvex dose-volume constraints. 2) Optimal delivery of the fluence map via leaf trajectory optimization, which has the potential to improve treatment plan quality while reducing the time needed to create a clinically acceptable treatment plan; and 3) A multi-therapy treatment pan scheduling using a Markov decision process that balances the treade-off between tumor control and normal-tissue complications, as oncolo
Pagination: all pages
URI: http://hdl.handle.net/10603/487681
Appears in Departments:Department of Electronics and Telecommunication

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01_title.pdfAttached File38 kBAdobe PDFView/Open
02_prelim pages.pdf1.24 MBAdobe PDFView/Open
03_content.pdf106.39 kBAdobe PDFView/Open
04_abstract.pdf419.85 kBAdobe PDFView/Open
05_chapter-1.pdf655.68 kBAdobe PDFView/Open
06_chapter-2.pdf418.87 kBAdobe PDFView/Open
07_chapter-3.pdf742.54 kBAdobe PDFView/Open
08_chapter-4.pdf689.44 kBAdobe PDFView/Open
09_chapter-5.pdf726.67 kBAdobe PDFView/Open
10_chapter-6.pdf957.41 kBAdobe PDFView/Open
11_chapter-7.pdf88.04 kBAdobe PDFView/Open
12_annexures.pdf684.98 kBAdobe PDFView/Open
80_recommendation.pdf125.07 kBAdobe PDFView/Open
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