Marchant, Tom, Skalski, Andrzej and Matuszewski, Bogdan (2012) Automatic tracking of implanted fiducial markers in cone beam CT projection images. Medical Physics, 39 (3). pp. 1322-1334. ISSN 0094-2405
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Official URL: http://dx.doi.org/10.1118/1.3684959
Purpose: This paper describes a novel method for simultaneous intrafraction tracking of multiple fiducial markers. Although the proposed method is generic and can be adopted for a number of applications including fluoroscopy based patient position monitoring and gated radiotherapy, the tracking results presented in this paper are specific to tracking fiducial markers in a sequence of cone beam CT projection images.
Methods: The proposed method is accurate and robust thanks to utilizing the mean shift and random sampling principles, respectively. The performance of the proposed method was evaluated with qualitative and quantitative methods, using data from two pancreatic and one prostate cancer patients and a moving phantom. The ground truth, for quantitative evaluation, was calculated based on manual tracking preformed by three observers.
Results: The average dispersion of marker position error calculated from the tracking results for pancreas data (six markers tracked over 640 frames, 3840 marker identifications) was 0.25 mm (at iscoenter), compared with an average dispersion for the manual ground truth estimated at 0.22 mm. For prostate data (three markers tracked over 366 frames, 1098 marker identifications), the average error was 0.34 mm. The estimated tracking error in the pancreas data was < 1 mm (2 pixels) in 97.6% of cases where nearby image clutter was detected and in 100.0% of cases with no nearby image clutter.
Conclusions: The proposed method has accuracy comparable to that of manual tracking and, in combination with the proposed batch postprocessing, superior robustness. Marker tracking in cone beam CT (CBCT) projections is useful for a variety of purposes, such as providing data for assessment of intrafraction motion, target tracking during rotational treatment delivery, motion correction of CBCT, and phase sorting for 4D CBCT.
|Uncontrolled Keywords (separate with ;):||cancer; computerised tomography; image sampling; medical image processing; phantoms; radiation therapy; random processes; image-guided radiotherapy; cone beam CT; marker tracking|
|Subjects:||Computer science > Software engineering|
Physical sciences > Physics
B - Subjects allied to medicine > B900 - Others in subjects allied to medicine
Engineering > Civil engineering
|Schools:||Faculty of Science and Technology > School of Engineering|
|Deposited By:||Bogdan Matuszewski|
|Deposited On:||28 Mar 2012 13:41|
|Last Modified:||17 May 2016 12:27|
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