Hidden seed reconstruction from C-arm images in brachytherapy

Ryan C. Kon, Ameet Kumar Jain, Gabor Fichtinger

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

Abstract

There has been a pressing clinical need for adaptive intraoperative dosimetry in the delivery of prostate brachytherapy implants. The missing prerequisite is the robust matching of the seeds across multiple C-arm images. This is further aggravated since seeds are invariably hidden in each image. We present a solution to recover these hidden seeds in this paper. A network flow formulation of the problem is proposed, where the desired solution is obtained (in polynomial time) by computing the flow with minimum cost. Phantom experiments show that using four X-ray images, on an average 99.8% of the seeds are recovered correctly, while simulations indicate that our algorithm is robust to segmentation errors of up to 1 mm and hidden seed rate of at least 8%. The results show strong feasibility and clinical data collection is currently underway.

Original languageEnglish (US)
Title of host publication2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
Pages526-529
Number of pages4
Volume2006
StatePublished - 2006
Event2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA, United States
Duration: Apr 6 2006Apr 9 2006

Other

Other2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Country/TerritoryUnited States
CityArlington, VA
Period4/6/064/9/06

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint

Dive into the research topics of 'Hidden seed reconstruction from C-arm images in brachytherapy'. Together they form a unique fingerprint.

Cite this