Using FPGA to Accelerate Monte Carlo Superposition Based Radiation Dose Calculation

Master's Thesis
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Abstract

Radiation Therapy (RT) is a major modality for treating cancer by delivering radiation dose to cancer cells. The Monte Carlo Superposition (MCS) method provides a fast but accurate algorithm for radiation dose calculation. However, it is still too slow to meet the ever-increasing speed requirement. This thesis seeks to accelerate the Monte Carlo Superposition algorithm by developing a cost-effective hardware solution based on a FPGA platform. For a hardware design, data representation is critical for system performance. This thesis proposes a general method for finding fixed point data representation for floating point algorithms. One random number generator and the two main steps of the Monte Carlo Superposition algorithm: in-phantom and Multi-Leaf Collimator (MLC) raytracing, are implemented. Performance analysis and those already completed works show that a good speedup of the hardware design over the original software design can be achieved.

Attributes

Attribute NameValues
URN
  • etd-12162009-081432

Author Yonghui Chen
Advisor Sharon Hu
Contributor Sharon Hu, Committee Chair
Contributor Danny Chen, Committee Co-Chair
Degree Level Master's Thesis
Degree Discipline Computer Science and Engineering
Degree Name MS
Defense Date
  • 2009-07-16

Submission Date 2009-12-16
Country
  • United States of America

Subject
  • FPGA

  • Monte carlo

  • supoposition

  • radiation dose calculation

Publisher
  • University of Notre Dame

Language
  • English

Record Visibility Public
Content License
  • All rights reserved

Departments and Units

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