@conference {Dehghan2016, title = {CT AND MRI FUSION FOR POSTIMPLANT PROSTATE BRACHYTHERAPY EVALUATION}, booktitle = {IEEE Int. Symp on Biomedical Imaging}, year = {2016}, month = {04/2016}, pages = {625-628}, abstract = {

Postoperative evaluation of prostate brachytherapy is typically
performed using CT, which does not have sufficient
soft tissue contrast for accurate anatomy delineation. MR-CT
fusion enables more accurate localization of both anatomy
and implanted radioactive seeds, and hence, improves the
accuracy of postoperative dosimetry. We propose a method
for automatic registration of MR and CT images without a
need for manual initialization. Our registration method employs
a point-to-volume registration scheme during which
localized seeds in the CT images, produced by commercial
treatment planning systems as part of the standard of care,
are rigidly registered to preprocessed MRI images. We tested
our algorithm on ten patient data sets and achieved an overall
registration error of 1.6 {\textpm} 0.8mm with a running time of less
than 20s. With high registration accuracy and computational
speed, and no need for manual intervention, our method has
the potential to be employed in clinical applications.

}, keywords = {Brachytherapy, Prostate}, author = {Ehsan Dehghan and Yi Le and Junghoon Lee and Danny Y Song and Gabor Fichtinger and Jerry L. Prince} } @article {Lee2008a, title = {Prostate brachytherapy seed localization with Gaussian blurring and camera self-calibration}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {11}, number = {Pt 2}, year = {2008}, pages = {636{\textendash}643}, publisher = {Department of Electrical, Computer Engineering, Johns Hopkins University, Baltimore, MD, USA}, abstract = {

A tomosynthesis-based prostate brachytherapy seed localization method is described Gaussian-blurred images are computed from a limited number of X-ray images, and a 3-D volume is reconstructed by backprojection Candidate seed locations are extracted from the reconstructed volume, false positive seeds are removed by optimizing a local cost function In case where the estimated pose error is large, a self-calibration process corrects the estimation error of the intrinsic camera parameters, the translation of the pose in order to improve the reconstruction Simulation, phantom experiment results imply that the implanted seed locations can be estimated from four or five images depending on the number of seeds The algorithm was also validated using patient data, successfully localizing the implanted seeds

}, keywords = {Artifacts, Brachytherapy, Calibration, Computer-Assisted, Humans, instrumentation/methods/standards, Male, methods, methods/standards, Normal Distribution, Prostatic Neoplasms, Radiographic Image Interpretation, radiography/radiotherapy, Radiotherapy, Tomography, X-Ray Computed}, author = {Junghoon Lee and Xiaofeng Liu and Jerry L. Prince and Gabor Fichtinger} }