Improved swarm intelligence solution in large scale radiation therapy inverse planning

Arezoo Modiri, Xuejun Gu, Aaron Hagan, Amit Sawant

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This study employs particle swarm optimization to solve the non-convex inverse problem of 4D stereotactic body radiation therapy planning, targeting toxicity reduction, for a right lower lobe lung tumor with motion range of 1.5cm. A novel approach is introduced to reduce the swarm search space. 90 aperture-weights are optimized using both conventional and improved PSO algorithms over 5 optimization runs per method. It is shown that, on average, the improved PSO-based plan reduces the maximum dose to heart, spinal cord and esophagus by 43%, as compared to the conventional PSO, while swarm population is cut to half.

Original languageEnglish (US)
Title of host publication2015 IEEE Great Lakes Biomedical Conference, GLBC 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479917921
DOIs
StatePublished - Jul 14 2015
Event36th IEEE Great Lakes Biomedical Conference, GLBC 2015 - Milwaukee, United States
Duration: May 14 2015May 17 2015

Other

Other36th IEEE Great Lakes Biomedical Conference, GLBC 2015
CountryUnited States
CityMilwaukee
Period5/14/155/17/15

Keywords

  • Optimization
  • Radiation therapy
  • stochastic

ASJC Scopus subject areas

  • Biotechnology
  • Civil and Structural Engineering

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