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A Computational Study on different penalty approaches for constrained optimization in radiation therapy treatment planning with a simulated annealing algorithm
Title
A Computational Study on different penalty approaches for constrained optimization in radiation therapy treatment planning with a simulated annealing algorithm.
Creator
Mohammadi Khoroushadi, Mohammad Sadegh, Shang, Charles, Ouhib, Zoubir, Graduate College, Leventouri, Theodora, Kalantzis, Georgios
Abstract/Description
Simulated Annealing algorithm is utilized for Intensity Modulated Radiation Therapy IMRT optimization. The goal in IMRT is to give the prescribed radiation dose to the tumor while minimizing the dose given to normal organs.
Date Issued
2015
PURL
http://purl.flvc.org/fau/fd/FA00005891
Format
Document (PDF)
Enhancement in Low-Dose Computed Tomography through Image Denoising Techniques: Wavelets and Deep Learning
Title
Enhancement in Low-Dose Computed Tomography through Image Denoising Techniques: Wavelets and Deep Learning.
Creator
Mohammadi Khoroushadi, Mohammad Sadegh, Leventouri, Theodora, Zhuang, Hanqi, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Physics
Abstract/Description
Reducing the amount of radiation in X-ray computed tomography has been an active area of research in the recent years. The reduction of radiation has the downside of degrading the quality of the CT scans by increasing the ratio of the noise. Therefore, some techniques must be utilized to enhance the quality of images. In this research, we approach the denoising problem using two class of algorithms and we reduce the noise in CT scans that have been acquired with 75% less dose to the patient...
Show moreReducing the amount of radiation in X-ray computed tomography has been an active area of research in the recent years. The reduction of radiation has the downside of degrading the quality of the CT scans by increasing the ratio of the noise. Therefore, some techniques must be utilized to enhance the quality of images. In this research, we approach the denoising problem using two class of algorithms and we reduce the noise in CT scans that have been acquired with 75% less dose to the patient compared to the normal dose scans. Initially, we implemented wavelet denoising to successfully reduce the noise in low-dose X-ray computed tomography (CT) images. The denoising was improved by finding the optimal threshold value instead of a non-optimal selected value. The mean structural similarity (MSSIM) index was used as the objective function for the optimization. The denoising performance of combinations of wavelet families, wavelet orders, decomposition levels, and thresholding methods were investigated. Results of this study have revealed the best combinations of wavelet orders and decomposition levels for low dose CT denoising. In addition, a new shrinkage function is proposed that provides better denoising results compared to the traditional ones without requiring a selected parameter. Alternatively, convolutional neural networks were employed using different architectures to resolve the same denoising problem. This new approach improved denoising even more in comparison to the wavelet denoising.
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Date Issued
2018
PURL
http://purl.flvc.org/fau/fd/FA00013115
Subject Headings
Tomography--Image quality, Wavelets (Mathematics), Deep learning, Tomography, X-Ray Computed
Format
Document (PDF)
A Computational Study on Different Penalty Approaches for Constrained Optimization in Radiation Therapy Treatment Planning with a Simulated Annealing Algorithm
Title
A Computational Study on Different Penalty Approaches for Constrained Optimization in Radiation Therapy Treatment Planning with a Simulated Annealing Algorithm.
Creator
Mohammadi Khoroushadi, Mohammad Sadegh, Kalantzis, Georgios, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Physics
Abstract/Description
Intensity modulated radiation therapy (IMRT) is a cancer treatment method in which the intensities of the radiation beams are modulated; therefore these beams have non-uniform radiation intensities. The overall result is the delivery of the prescribed dose in the target volume. The dose distribution is conformal to the shape of the target and minimizes the dose to the nearby critical organs. An inverse planning algorithm is used to obtain those non-uniform beam intensities. In inverse...
Show moreIntensity modulated radiation therapy (IMRT) is a cancer treatment method in which the intensities of the radiation beams are modulated; therefore these beams have non-uniform radiation intensities. The overall result is the delivery of the prescribed dose in the target volume. The dose distribution is conformal to the shape of the target and minimizes the dose to the nearby critical organs. An inverse planning algorithm is used to obtain those non-uniform beam intensities. In inverse treatment planning, the treatment plan is achieved by using an optimization process. The optimized plan results to a high-quality dose distribution in the planning target volume (PTV), which receives the prescribed dose while the dose that is received by the organs at risk (OARs) is reduced. Accordingly, an objective function has to be defined for the PTV, while some constraints have to be considered to handle the dose limitations for the OARs.
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Date Issued
2016
PURL
http://purl.flvc.org/fau/fd/FA00004765
Subject Headings
Image-guided radiation therapy., Radiation--Dosage., Mathematical optimization., Evolutionary programming (Computer science), Medical physics., Medical radiology--Data processing.
Format
Document (PDF)