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Premium Prostate implant reconstruction from C‐arm images with motion‐compensated tomosynthesis
Dehghan Ehsan,
Moradi Mehdi,
Wen Xu,
French Danny,
Lobo Julio,
Morris W. James,
Salcudean Septimiu E.,
Fichtinger Gabor
Publication year2011
Publication title
medical physics
Resource typeJournals
PublisherAmerican Association of Physicists in Medicine
Purpose: Accurate localization of prostate implants from several C‐arm images is necessary for ultrasound‐fluoroscopy fusion and intraoperative dosimetry. The authors propose a computational motion compensation method for tomosynthesis‐based reconstruction that enables 3D localization of prostate implants from C‐arm images despite C‐arm oscillation and sagging. Methods: Five C‐arm images are captured by rotating the C‐arm around its primary axis, while measuring its rotation angle using a protractor or the C‐arm joint encoder. The C‐arm images are processed to obtain binary seed‐only images from which a volume of interest is reconstructed. The motion compensation algorithm, iteratively, compensates for 2D translational motion of the C‐arm by maximizing the number of voxels that project on a seed projection in all of the images. This obviates the need for C‐arm full pose tracking traditionally implemented using radio‐opaque fiducials or external trackers. The proposed reconstruction method is tested in simulations, in a phantom study and on ten patient data sets. Results: In a phantom implanted with 136 dummy seeds, the seed detection rate was 100% with a localization error of 0.86 ± 0.44 mm (Mean ± STD) compared to CT. For patient data sets, a detection rate of 99.5% was achieved in approximately 1 min per patient. The reconstruction results for patient data sets were compared against an available matching‐based reconstruction method and showed relative localization difference of 0.5 ± 0.4 mm. Conclusions: The motion compensation method can successfully compensate for large C‐arm motion without using radio‐opaque fiducial or external trackers. Considering the efficacy of the algorithm, its successful reconstruction rate and low computational burden, the algorithm is feasible for clinical use.
Subject(s)algorithm , artificial intelligence , breast cancer , cancer , computer science , computer vision , fiducial marker , fluoroscopy , imaging phantom , iterative reconstruction , mammography , match moving , medicine , motion (physics) , motion compensation , nuclear medicine , projection (relational algebra) , radiology , robotic arm , tomosynthesis , voxel
SCImago Journal Rank1.473

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