Prostate brachytherapy seed reconstruction with Gaussian blurring and optimal coverage cost

Junghoon Lee, Xiaofeng Liu, Ameet K. Jain, Danny Y. Song, Everette C. Burdette, Jerry L. Prince, Gabor Fichtinger

Research output: Contribution to journalArticle

Abstract

Intraoperative dosimetry in prostate brachytherapy requires localization of the implanted radioactive seeds. A tomosynthesis-based seed reconstruction method is proposed. A three-dimensional volume is reconstructed from Gaussian-blurred projection images and candidate seed locations are computed from the reconstructed volume. A false positive seed removal process, formulated as an optimal coverage problem, iteratively removes ghost seeds that are created by tomosynthesis reconstruction. In an effort to minimize pose errors that are common in conventional C-arms, initial pose parameter estimates are iteratively corrected by using the detected candidate seeds as fiducials, which automatically focuses the collected images and improves successive reconstructed volumes. Simulation results imply that the implanted seed locations can be estimated with a detection rate of ≥97.9% and ≥99.3% from three and four images, respectively, when the C-arm is calibrated and the pose of the C-arm is known. The algorithm was also validated on phantom data sets successfully localizing the implanted seeds from four or five images. In a Phase-1 clinical trial, we were able to localize the implanted seeds from five intraoperative fluoroscopy images with 98.8% ( STD=1.6) overall detection rate.

Original languageEnglish (US)
Article number5165026
Pages (from-to)1955-1968
Number of pages14
JournalIEEE transactions on medical imaging
Volume28
Issue number12
DOIs
StatePublished - Dec 2009

Keywords

  • Brachytherapy
  • C-arm auto-focusing
  • Gaussian blurring
  • Optimal coverage cost
  • Prostate cancer
  • Tomosynthesis

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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