Models for predicting objective function weights in prostate cancer IMRT
نویسندگان
چکیده
منابع مشابه
Models for predicting objective function weights in prostate cancer IMRT.
PURPOSE To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. METHODS A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for ...
متن کاملIMRT for prostate cancer
The increased frequency of PSA testing has led to an increased diagnosis of early organ confined prostate cancer. Diagnosis is primarily made by histology, via TRUS-guided sextant biopsy or template biopsy which can provide improved localisation of cancer within the prostate. Staging is from digital rectal examination, from imaging with multi-parametric MRI (TNM staging), from PSA levels, and f...
متن کاملComparison between two different methods used for IMRT plans QA of Prostate cancer
Introduction: The aim of this study is evaluation of two Quality Assurance methods in sliding window IMRT technique and Determination of gamma index in both methods Materials and Methods: In this study two tools named" Delta4" phantom and " Epiqa" software has been used to perform QA on the treatment plan before the actual treatment by Varian linear acceler...
متن کاملStereotactic IMRT for prostate cancer: Dosimetric impact of multileaf collimator leaf width in the treatment of prostate cancer with IMRT
The focus of this work is the dosimetric impact of multileaf collimator (MLC) leaf width on the treatment of prostate cancer with intensity-modulated radiation therapy (IMRT). Ten patients with prostate cancer were planned for IMRT delivery using two different MLC leaf widths--4mm and 10mm--representing the Radionics micro-multileaf collimator (mMLC) and Siemens MLC, respectively. Treatment pla...
متن کاملDetermining The Optimal Weights In Multiple Objective Function Optimization
An important problem in computer vision is the determination of weights for multiple objective function optimization. This problem arises naturally in many reconstruction problems, where one wishes to reconstruct a function belonging to a constrained class of signals based upon noisy observed data. A common approach is to combine the objective functions into a single total cost function. The pr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Medical Physics
سال: 2015
ISSN: 0094-2405
DOI: 10.1118/1.4914140