Hadi Tadayyon

@article{Tadayyon2011,

title = {Target Motion Tracking in MRI-guided Transrectal Robotic Prostate Biopsy},

author = {Hadi Tadayyon and Andras Lasso and Aradhana Kaushal and Peter Guion and Gabor Fichtinger},

url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Tadayyon2011.pdf},

doi = {10.1109/TBME.2011.2163633},

issn = {0018-9294},

year  = {2011},

date = {2011-08-01},

urldate = {2011-08-01},

journal = {IEEE Transactions on Biomedical Engineering},

volume = {58},

pages = {3135-42},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{fichtinger2011i,

title = {Target motion tracking in MRI-guided transrectal robotic prostate biopsy},

author = {Hadi Tadayyon and Andras Lasso and Aradhana Kaushal and Peter Guion and Gabor Fichtinger},

url = {https://ieeexplore.ieee.org/abstract/document/5975205/},

year  = {2011},

date = {2011-01-01},

journal = {IEEE transactions on biomedical engineering},

volume = {58},

issue = {11},

pages = {3135-3142},

publisher = {IEEE},

abstract = {Purpose 

MRI-guided prostate needle biopsy requires compensation for organ motion between target planning and needle placement. Two questions are studied and answered in this paper: 1) is rigid registration sufficient in tracking the targets with an error smaller than the clinically significant size of prostate cancer and 2) what is the effect of the number of intraoperative slices on registration accuracy and speed? 

Methods 

we propose multislice-to-volume registration algorithms for tracking the biopsy targets within the prostate. Three orthogonal plus additional transverse intraoperative slices are acquired in the approximate center of the prostate and registered with a high-resolution target planning volume. Both rigid and deformable scenarios were implemented. Both simulated and clinical MRI-guided robotic prostate biopsy data were used to assess tracking accuracy. 

Results 

average registration errors in clinical …},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{fichtinger2010o,

title = {Target motion compensation in MRI-guided prostate biopsy with static images},

author = {Hadi Tadayyon and Andras Lasso and Sean Gill and Aradhana Kaushal and Peter Guion and Gabor Fichtinger},

url = {https://ieeexplore.ieee.org/abstract/document/5626497/},

year  = {2010},

date = {2010-01-01},

pages = {5416-5419},

publisher = {IEEE},

abstract = {Purpose 

MRI-guided prostate needle biopsy requires compensation for organ motion between target planning and needle placement. 

Methods 

We propose slice-to-volume registration algorithms for tracking the prostate motion. Three orthogonal intra-operative slices are acquired in the approximate center of the prostate and registered with a high-resolution target planning volume. Both rigid and deformable scenarios were implemented. MRI-guided robotic prostate biopsy cases were analyzed retrospectively. 

Results 

Average registration errors were 2.55mm for the rigid algorithm and 2.05mm for the deformable algorithm. 

Conclusion 

Slice-based tracking appears to be promising. Deformable registration does not seem warranted.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{fichtinger2010w,

title = {MRI-guided prostate motion tracking by means of multislice-to-volume registration},

author = {Hadi Tadayyon and Siddharth Vikal and Sean Gill and Andras Lasso and Gabor Fichtinger},

url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/7625/76252V/MRI-GUIDED-prostate-motion-tracking-by-means-of-multislice-to/10.1117/12.844454.short},

year  = {2010},

date = {2010-01-01},

volume = {7625},

pages = {904-911},

publisher = {SPIE},

abstract = {We developed an algorithm for tracking prostate motion during MRI-guided prostatic needle placement, with the primary application in prostate biopsy. Our algorithm has been tested on simulated patient and phantom data. The algorithm features a robust automatic restart and a 12-core biopsy error validation scheme. Simulation tests were performed on four patient MRI pre-operative volumes. Three orthogonal slices were extracted from the pre-operative volume to simulate the intra-operative volume and a volume of interest was defined to isolate the prostate. Phantom tests used six datasets, each representing the phantom at a known perturbed position. These volumes were registered to their corresponding reference volume (the phantom at its home position). Convergence tests on the phantom data showed that the algorithm demonstrated accurate results at 100% confidence level for initial misalignments of less …},

keywords = {},

pubstate = {published},

tppubtype = {article}

}