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A Fuzzy-Based Approach for Optimizing Dose Distribution in High-Dose-Rate Prostate Brachytherapy Using Multi-Objective Evolutionary Algorithms
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چکیده: (12 مشاهده) |
Prostate cancer is the most common cancer in men and the second leading cause of cancer-related death worldwide. Over the years, researchers from various fields, beyond medicine, have sought to expand their understanding of the disease to develop more effective treatments. Treatment planning for high-dose-rate (HDR) brachytherapy involves designing the trajectory of the radiation source to deliver sufficient doses to the target area while minimizing exposure to surrounding organs at risk (OAR) within clinically safe limits. Since the exact tumor volume is not known, the model uses gray numbers instead of tumor volume, which provides more accurate results.
In this study, four powerful multi-objective evolutionary algorithms (MOEAs) NSGA1-II, PESA2-II, SPEA3-II, and MOPSO4 are employed. Instead of yielding a single best solution, these algorithms produce a set of Pareto-optimal solutions, each representing a trade-off where no one solution is definitively better than the rest. However, they demonstrate improved performance compared to other optimization methods. The results show that the MOPSO algorithm performs better than the other three powerful algorithms in terms of solution quality and maintaining diversity among solutions.
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نوع مطالعه: پژوهشی |
موضوع مقاله:
Fuzzy Sets and Systems
دریافت: 1404/5/20 | پذیرش: 1404/7/18 | انتشار: 1404/7/18
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