TY - JOUR
T1 - Point-to-volume registration of prostate implants to ultrasound
AU - Dehghan, Ehsan
AU - Lee, Junghoon
AU - Fallavollita, Pascal
AU - Kuo, Nathanael
AU - Deguet, Anton
AU - Burdette, E. Clif
AU - Song, Danny
AU - Prince, Jerry L.
AU - Fichtinger, Gabor
N1 - Funding Information:
E. Dehghan was supported as an Ontario Ministry of Research and Innovation Fellow. G. Fichtinger was supported as Cancer Care Ontario Research Chair. This work was also supported by National Institutes of Health/National Cancer Institute (NIH/NCI) under Grants 2R44CA099374 and 1R01CA151395.
PY - 2011
Y1 - 2011
N2 - Ultrasound-Fluoroscopy fusion is a key step toward intra-operative dosimetry for prostate brachytherapy. We propose a method for intensity-based registration of fluoroscopy to ultrasound that obviates the need for seed segmentation required for seed-based registration. We employ image thresholding and morphological and Gaussian filtering to enhance the image intensity distribution of ultrasound volume. Finally, we find the registration parameters by maximizing a point-to-volume similarity metric. We conducted an experiment on a ground truth phantom and achieved registration error of 0.7±0.2mm. Our clinical results on 5 patient data sets show excellent visual agreement between the registered seeds and the ultrasound volume with a seed-to-seed registration error of 1.8±0.9mm. With low registration error, high computational speed and no need for manual seed segmentation, our method is promising for clinical application.
AB - Ultrasound-Fluoroscopy fusion is a key step toward intra-operative dosimetry for prostate brachytherapy. We propose a method for intensity-based registration of fluoroscopy to ultrasound that obviates the need for seed segmentation required for seed-based registration. We employ image thresholding and morphological and Gaussian filtering to enhance the image intensity distribution of ultrasound volume. Finally, we find the registration parameters by maximizing a point-to-volume similarity metric. We conducted an experiment on a ground truth phantom and achieved registration error of 0.7±0.2mm. Our clinical results on 5 patient data sets show excellent visual agreement between the registered seeds and the ultrasound volume with a seed-to-seed registration error of 1.8±0.9mm. With low registration error, high computational speed and no need for manual seed segmentation, our method is promising for clinical application.
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U2 - 10.1007/978-3-642-23629-7_75
DO - 10.1007/978-3-642-23629-7_75
M3 - Conference article
C2 - 21995080
AN - SCOPUS:80053527136
SN - 0302-9743
VL - 6892 LNCS
SP - 615
EP - 622
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
IS - PART 2
T2 - 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011
Y2 - 18 September 2011 through 22 September 2011
ER -