Radiotherapy Evolutionary Algorithm Further 2d Pareto-Multi Objective Optimization with Biological Effective Model for Head-Neck Cancer Hyperfractionated Treatment

Autor: Francisco Casesnoves
Rok vydání: 2023
Předmět:
Pareto-Multiobjective Optimization (PMO)
Mathematical Methods (MM)
Biological Models (BM)
Radiation Therapy (RT)
Initial Tumor Clonogenes Number Population ( N0)
Effective Tumor Population Clonogenes Number ( NEffective )
Linear Quadratic Model (LQM)
Integral Equation (IE)
Tumor Control Probability (TCP)
Normal Tissue Complications Probability (NTCP)
Biological Effective model (BED)
Tumor Control Cumulative Probability (TCCP)
Radiation Photon-Dose (RPD)
Nonlinear Optimization
Radiotherapy Treatment Planning Optimization (TPO)
Source-Surface Distance (SSD)
Software Engineering Methods
Radiation Photon-Dose
Attenuation Exponential Factor (AEF)
Nonlinear Optimization
Radiotherapy Wedge Filter (WF)
Anisotropic Analytic Model (AAA)
Fluence Factor (FF)
Omega Factor (OF)
Treatment Planning Optimization (TPO)
Breast Tumor (BT)
Artificial Intelligence (AI)
Pareto-MultiobjectiveOptimization (PMO)
Genetic Algorithms (GA)
DOI: 10.5281/zenodo.7878728
Popis: Constrained algorithms for BED model (Biological Effective Dose) in Head and Neck tumors Hypofractionation TPO optimized with Pareto-Multiobjective (PMO) Genetic Algorithms (GA) software are obtained. The mathematical method for constrained GA is applied for a number of series of Pareto Functions. Results demonstrate PMO-AI imaging process sequences and extensive numerical values of PMO Head and Neck cancer parameters. Comparison and review with simple constrained GA Optimization is presented. Improved RT Head and Neckcancer TPO, and tumors in general for Fractional-dose photon dose delivery are explained in brief
Databáze: OpenAIRE
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