Development of a robust MRI fiducial system for automated fusion of MR-US abdominal images

Christopher P. Favazza, Krzysztof R. Gorny, Matthew R. Callstrom, Anil N. Kurup, Michael Washburn, Pamela S. Trester, Charles L. Fowler, Nicholas J. Hangiandreou

Research output: Contribution to journalArticlepeer-review


We present the development of a two-component magnetic resonance (MR) fiducial system, that is, a fiducial marker device combined with an auto-segmentation algorithm, designed to be paired with existing ultrasound probe tracking and image fusion technology to automatically fuse MR and ultrasound (US) images. The fiducial device consisted of four ~6.4 mL cylindrical wells filled with 1 g/L copper sulfate solution. The algorithm was designed to automatically segment the device in clinical abdominal MR images. The algorithm's detection rate and repeatability were investigated through a phantom study and in human volunteers. The detection rate was 100% in all phantom and human images. The center-of-mass of the fiducial device was robustly identified with maximum variations of 2.9 mm in position and 0.9° in angular orientation. In volunteer images, average differences between algorithm-measured inter-marker spacings and actual separation distances were 0.53 ± 0.36 mm. “Proof-of-concept” automatic MR-US fusions were conducted with sets of images from both a phantom and volunteer using a commercial prototype system, which was built based on the above findings. Image fusion accuracy was measured to be within 5 mm for breath-hold scanning. These results demonstrate the capability of this approach to automatically fuse US and MR images acquired across a wide range of clinical abdominal pulse sequences.

Original languageEnglish (US)
Pages (from-to)261-270
Number of pages10
JournalJournal of applied clinical medical physics
Issue number4
StatePublished - Jul 2018


  • MRI
  • auto-registration
  • fiducial marker
  • image fusion
  • ultrasound

ASJC Scopus subject areas

  • Radiation
  • Instrumentation
  • Radiology Nuclear Medicine and imaging


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