Rotated principal components for fuzzy segmentation szinitiggraphic time series in individual dose planing

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1 Citation (Scopus)

Abstract

Time activity curves are assessed from whole body szintigraphic time series for individual dose estimation to limit the applicable therapeutic dose, preventing critical organs from substantial damage during radiation therapy. Whole body scans are projective images, thus organ ROIs may overlap. After careful image registration rotated principal components analysis is applied to the time series, identifying image parts with similar dynamics. This method allows the separation of overlapping structures providing fuzzy regions, where fractions of the pixel counts are assigned to the respective accumulating morphology. The summed counts from theses fuzzy regions are modified with the physical decay constant of the considered therapeutic isotope, providing the correct time samples for further dose calculation. Mono-or bi-exponential regression yields the time activity curves for the respective morphologies, passed to a standard dose calculation program. The newly developed method allows the fuzzy separation of overlapping structures in projective planar imaging series, yielding more accurate dose calculation in individual radiation therapy.

Original languageEnglish
Title of host publication4th International Workshop on Innovative Simulation for Health Care, IWISH 2015
EditorsFrancesco Longo, Marco Frascio, Vera Novak, Jerzy W. Rozenblit, Yury Merkuryev, Agostino G. Bruzzone
PublisherDIME UNIVERSITY OF GENOA
Pages33-37
Number of pages5
ISBN (Electronic)9788897999539
Publication statusPublished - 2015
Event4th International Workshop on Innovative Simulation for Health Care, IWISH 2015 - Bergeggi, Italy
Duration: 21 Sep 201523 Sep 2015

Publication series

Name4th International Workshop on Innovative Simulation for Health Care, IWISH 2015

Conference

Conference4th International Workshop on Innovative Simulation for Health Care, IWISH 2015
CountryItaly
CityBergeggi
Period21.09.201523.09.2015

Keywords

  • Dose planning
  • Factor analysis
  • Image registration
  • Regression

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