Open AccessDevelopment of a robust MRI fiducial system for automated fusion of MR ‐ US abdominal images
Author(s) -
Favazza Christopher P.,
Gorny Krzysztof R.,
Callstrom Matthew R.,
Kurup Anil N.,
Washburn Michael,
Trester Pamela S.,
Fowler Charles L.,
Hangiandreou Nicholas J.
Publication year - 2018
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1002/acm2.12352
Subject(s) - fiducial marker , imaging phantom , segmentation , magnetic resonance imaging , computer science , image fusion , artificial intelligence , nuclear medicine , fuse (electrical) , computer vision , repeatability , medicine , image (mathematics) , physics , mathematics , radiology , statistics , quantum mechanics
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.