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Optimal Matching for Prostate Brachytherapy Seed Localization with Dimension Reduction

  • Junghoon Lee
  • Christian Labat
  • Ameet K. Jain
  • Danny Y. Song
  • Everette C. Burdette
  • Gabor Fichtinger
  • Jerry L. Prince
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5761)

Abstract

In prostate brachytherapy, x-ray fluoroscopy has been used for intra-operative dosimetry to provide qualitative assessment of implant quality. More recent developments have made possible 3D localization of the implanted radioactive seeds. This is usually modeled as an assignment problem and solved by resolving the correspondence of seeds. It is, however, NP-hard, and the problem is even harder in practice due to the significant number of hidden seeds. In this paper, we propose an algorithm that can find an optimal solution from multiple projection images with hidden seeds. It solves an equivalent problem with reduced dimensional complexity, thus allowing us to find an optimal solution in polynomial time. Simulation results show the robustness of the algorithm. It was validated on 5 phantom and 18 patient datasets, successfully localizing the seeds with detection rate of ≥ 97.6 % and reconstruction error of ≤ 1.2 mm. This is considered to be clinically excellent performance.

Keywords

Dimensionality Reduction Reconstruction Error Seed Image Optimal Match Reconstruction Accuracy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Junghoon Lee
    • 1
  • Christian Labat
    • 2
  • Ameet K. Jain
    • 3
  • Danny Y. Song
    • 4
  • Everette C. Burdette
    • 5
  • Gabor Fichtinger
    • 2
    • 6
  • Jerry L. Prince
    • 1
  1. 1.Department of Electrical and Computer Eng.Johns Hopkins UniversityUSA
  2. 2.Department of Computer ScienceJohns Hopkins UniversityUSA
  3. 3.Philips Research North AmericaUSA
  4. 4.Department of Radiation OncologyJohns Hopkins School of MedicineUSA
  5. 5.Acoustic MedSystems, Inc.USA
  6. 6.School of ComputingQueen’s UniversityCanada

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