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Configurable Automatic Detection and Registration of Fiducial Frames for Device-to-Image Registration in MRI-guided Prostate Interventions

Institution:
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA.
Publisher:
Int Conf Med Image Comput Comput Assist Interv. MICCAI 2013
Publication Date:
Sep-2013
Volume Number:
16
Issue Number:
Pt 3
Pages:
355-62
Citation:
Int Conf Med Image Comput Comput Assist Interv. 2013 Sep;16(Pt 3):355-62.
PubMed ID:
24505781
PMCID:
PMC4009697
Appears in Collections:
SNR, NCIGT, Prostate Group, SLICER
Sponsors:
R01 CA111288/CA/NCI NIH HHS/United States
P01 CA067165/CA/NCI NIH HHS/United States
P41 RR019703/RR/NCRR NIH HHS/United States
P41 EB015898/EB/NIBIB NIH HHS/United States
R01 CA124377/CA/NCI NIH HHS/United States
R01 CA138586/CA/NCI NIH HHS/United States
Center for Integration of Medicine and Innovative Technology (CIMIT 11-325)
Siemens Seed Grant Award
Generated Citation:
Tokuda J., Song S-E., Tuncali K., Tempany C.M., Hata N. Configurable Automatic Detection and Registration of Fiducial Frames for Device-to-Image Registration in MRI-guided Prostate Interventions. Int Conf Med Image Comput Comput Assist Interv. 2013 Sep;16(Pt 3):355-62. PMID: 24505781. PMCID: PMC4009697.
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We propose a novel automatic fiducial frame detection and registration method for device-to-image registration in MRI-guided prostate interventions. The proposed method does not require any manual selection of markers, and can be applied to a variety of fiducial frames, which consist of multiple cylindrical MR-visible markers placed in different orientations. The key idea is that automatic extraction of linear features using a line filter is more robust than that of bright spots by thresholding; by applying a line set registration algorithm to the detected markers, the frame can be registered to the MRI. The method was capable of registering the fiducial frame to the MRI with an accuracy of 1.00 ± 0.73 mm and 1.41 ± 1.06 degrees in a phantom study, and was sufficiently robust to detect the fiducial frame in 98% of images acquired in clinical cases despite the existence of anatomical structures in the field of view.

Additional Material
1 File (70.114kB)
Tokuda-MICCAI2013-fig2.jpg (70.114kB)