Fast gamma-ray event interaction position estimation using k-d tree - A simulation study

Xin Li, Li Tao, Craig S. Levin, Lars R. Furenlid

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

Abstract

We have developed a gamma-ray interaction-position estimation method using k-d tree search, which can achieve efficiency and accuracy at the same time. This method can be combined with various kinds of closeness metrics such as Euclidean distance, and maximum-likelihood estimation. The time complexity of the k-d tree search method is O(log2(N)), where N represents the number of entries in the reference data set. The accuracy of the k-d tree search is equivalent to that of the exhaustive search method which has the highest achievable accuracy. Most importantly, this method has no requirement on the shapes of mean-detector-response functions (MDRFs), which means that it is also very robust, and can be applied widely without restrictions.

Original languageEnglish (US)
Title of host publication2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538684948
DOIs
StatePublished - Nov 2018
Event2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Sydney, Australia
Duration: Nov 10 2018Nov 17 2018

Publication series

Name2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings

Conference

Conference2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018
CountryAustralia
CitySydney
Period11/10/1811/17/18

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Nuclear and High Energy Physics

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