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Updated: May 3, 2026
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
Published on: October 27, 2023
Configurable automatic detection and registration of fiducial frames for device-to-image registration in MRI-guided
Junichi Tokuda1, Sang-Eun Song2, Kemal Tuncali2
1Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. tokuda@bwh.harvard.edu
Abstract:
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.
