Paper
11 May 1994 Automatic technique for localizing externally attached markers in MR and CT volume images of the head
Matthew Yang Wang, J. Michael Fitzpatrick, Calvin R. Maurer Jr., Robert J. Maciunas
Author Affiliations +
Abstract
An image processing technique is presented here for finding centroids of cylindrical fiducial markers attached externally to the human head in CT and MR volume images. The centroids can be used for image registration. The technique, which is fast, automatic, and knowledge-based, has two major steps. First, it searches the whole image volume to find all markerlike objects and gets a position inside each object. We call this position a 'seed' point, and we call the object a candidate marker. Second, it selects the voxels surrounding the seed voxel as marker or non-marker voxels using knowledge-based rules and provides an intensity weighted centroid for each true marker. We call this final centroid the 'fiducial' point of the marker. The technique has been developed on forty-two scans of six patients -- one CT and six MR scans per patient. There were four markers attached to each patient for a total of 168 marker images. On these images the technique exhibits no false positives or false negatives for CT. For MR the false positive rate and the false negative rate are both 1.4%. To evaluate the accuracy of the fiducial points MR-CT registration was performed using geometrical correction for the MR images. The fiducial registration accuracies averaged 0.4 mm and were better that 0.6 mm on each of the eighteen image pairs.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Matthew Yang Wang, J. Michael Fitzpatrick, Calvin R. Maurer Jr., and Robert J. Maciunas "Automatic technique for localizing externally attached markers in MR and CT volume images of the head", Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); https://doi.org/10.1117/12.175056
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Cited by 7 scholarly publications.
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KEYWORDS
Magnetic resonance imaging

Computed tomography

Image registration

Head

Image processing

Binary data

Image segmentation

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