Publications

@article{Boctor2006a,

title = {Bootstrapped ultrasound calibration},

author = {Emad Boctor and Iulian Iordachita and Michael Choti and Gregory D. Hager and Gabor Fichtinger},

year  = {2006},

date = {2006-01-01},

urldate = {2006-01-01},

journal = {Studies in health technology and informatics},

volume = {119},

pages = {61–66},

publisher = {Engineering Research Center, Johns Hopkins University, USA},

abstract = {<p>This paper introduces an enhanced (bootstrapped) method for tracked ultrasound probe calibration Prior to calibration, a position sensor is used to track an ultrasound probe in 3D space, while the US image is used to determine calibration target locations within the image From this information, an estimate of the transformation matrix of the scan plane with respect to the position sensor is computed While all prior calibration methods terminate at this phase, we use this initial calibration estimate to bootstrap an additional optimization of the transformation matrix on independent data to yield the minimum reconstruction error on calibration targets The bootstrapped workflow makes use of a closed-form calibration solver, associated sensitivity analysis, allowing for rapid, robust convergence to an optimal calibration matrix Bootstrapping demonstrates superior reconstruction accuracy</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Jain2006a,

title = {C-arm tracking and reconstruction without an external tracker},

author = {Ameet K. Jain and Gabor Fichtinger},

url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Jain2006a.pdf},

year  = {2006},

date = {2006-01-01},

urldate = {2006-01-01},

journal = {Medical image computing and computer-assisted intervention (MICCAI)},

volume = {9},

number = {Pt 1},

pages = {494–502},

publisher = {Department of Computer Science, Johns Hopkins University, USA},

abstract = {<p>For quantitative C-arm fluoroscopy, we have developed a unified mathematical framework to tackle the issues of intra-operative calibration, pose estimation, correspondence, reconstruction, without the use of optical/electromagnetic trackers or precision-made fiducial fixtures Our method uses randomly distributed unknown points in the imaging volume, either naturally present or induced by randomly sticking beads or other simple markers in the image pace After these points are segmented, a high dimensional non-linear optimization computes all unknown parameters for calibration, C-arm pose, correspondence, reconstruction Preliminary phantom experiments indicate an average C-arm tracking accuracy of 0 9 degrees, a 3D reconstruction error of 0 8 mm, with an 80 region of convergence for both the AP, lateral axes The method appears to be sufficiently accurate for many clinical applications, and appealing since it works without any external instrumentation, does not interfere with the workspace</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kazanzides2006,

title = {Design, validation of an image-guided robot for small animal research},

author = {Peter Kazanzides and Jenghwa Chang and Iulian Iordachita and Jack Li and Clifton Ling and Gabor Fichtinger},

url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Kazanzides2006a.pdf},

year  = {2006},

date = {2006-01-01},

urldate = {2006-01-01},

journal = {Medical image computing and computer-assisted intervention (MICCAI)},

volume = {9},

number = {Pt 1},

pages = {50–57},

publisher = {Department of Computer Science, Johns Hopkins University, USA pkaz@jhu edu},

abstract = {<p>We developed an image-guided robot system to achieve highly accurate placement of thin needles, probes into in-vivo rodent tumor tissue in a predefined pattern that is specified on a preoperative image This system can be used for many experimental procedures where the goal is to correlate a set of physical measurements with a corresponding set of image intensities or, more generally, to perform a physical action at a set of anatomic points identified on a preoperative image This paper focuses on the design, validation of the robot system, where the first application is to insert oxygen measurement probes in a three-dimensional (3D) grid pattern defined with respect to a PET scan of a tumor The design is compatible with CT, MRI, which we plan to use to identify targets for biopsy, for the injection of adenoviral sequences for gene therapy The validation is performed using a phantom, includes a new method for estimating the Fiducial Localization Error (FLE) based on the measured Fiducial Distance Error (FDE)</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Fischer2006,

title = {MRI image overlay: applications to arthrography needle insertion},

author = {Gregory Fischer and Anton Degeut and Daniel Schlattman and Russell H. Taylor and Laura Fayad and James Zinreich and Gabor Fichtinger},

year  = {2006},

date = {2006-01-01},

urldate = {2006-01-01},

journal = {Studies in health technology and informatics},

volume = {119},

pages = {150–155},

abstract = {<p>Magnetic Resonance Imaging (MRI) has unmatched potential for planning, guiding, monitoring, controlling interventions MR arthrography (MRA) is the imaging gold standard to assess small ligament, fibrocartilage injury in joints In contemporary practice, MRA consists of two consecutive sessions: 1) an interventional session where a needle is driven to the joint space, gadolinium contrast is injected under fluoroscopy or CT guidance 2) A diagnostic MRI imaging session to visualize the distribution of contrast inside the joint space, evaluate the condition of the joint Our approach to MRA is to eliminate the separate radiologically guided needle insertion, contrast injection procedure by performing those tasks on conventional high-field closed MRI scanners We propose a 2D augmented reality image overlay device to guide needle insertion procedures This approach makes diagnostic high-field magnets available for interventions without a complex, expensive engineering entourage</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DiMaio2006,

title = {Needle artifact localization in 3T MR images},

author = {Simon DiMaio and Daniel Kacher and Randy Ellis and Gabor Fichtinger and Nobuhiko Hata and Gary Zientara and Lawrence Panych and Ron Kikinis and Ferenc Jolesz},

url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/DiMaio2006c.pdf},

year  = {2006},

date = {2006-01-01},

urldate = {2006-01-01},

journal = {Studies in health technology and informatics},

volume = {119},

pages = {120–125},

publisher = {Brigham, Women’s Hospital, Harvard Medical School, Boston 02115, USA simond@bwh harvard edu},

abstract = {<p>This work explores an image-based approach for localizing needles during MRI-guided interventions, for the purpose of tracking, navigation Susceptibility artifacts for several needles of varying thickness were imaged, in phantoms, using a 3 tesla MRI system, under a variety of conditions The relationship between the true needle positions, the locations of artifacts within the images, determined both by manual, automatic segmentation methods, have been quantified, are presented here</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DiMaio2006b,

title = {Robot-assisted needle placement in open-MRI: system architecture, integration and validation},

author = {Simon DiMaio and Steve Pieper and Kiyoyuki Chinzei and Nobuhiko Hata and Emese Balogh and Gabor Fichtinger and Clare M Tempany and Ron Kikinis},

url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/DiMaio2006b.pdf},

year  = {2006},

date = {2006-01-01},

urldate = {2006-01-01},

journal = {Studies in health technology and informatics},

volume = {119},

pages = {126–131},

publisher = {Brigham, Women’s Hospital, Harvard Medical School, USA simond@bwh harvard edu},

abstract = {<p>This work describes an integrated system for planning, performing percutaneous procedures-such as prostate biopsy-with robotic assistance under MRI-guidance The physician interacts with a planning interface in order to specify the set of desired needle trajectories, based on anatomical structures, lesions observed in the patient’s MR images All image-space coordinates are automatically computed, and used to position a needle guide by means of an MRI-compatible robotic manipulator, thus avoiding the limitations of the traditional fixed needle template Direct control of real-time imaging aids visualization of the needle as it is manually inserted through the guide Results from in-scanner phantom experiments are provided</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kennedy2006,

title = {Robotically Assisted Needle Placement for Prostate Brachytherapy},

author = {Christopher Kennedy and Iulian Iordachita and E. Clif Burdette and Gernot Kronreif and Wolfgang Ptacek and Peter Kazanzides and Danny Y Song and Gabor Fichtinger},

url = {http://link aip org/link/?MPH/33/2264/3

https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Kennedy2006.pdf},

doi = {10 1118/1 2241837},

year  = {2006},

date = {2006-01-01},

urldate = {2006-01-01},

journal = {Journal of Medical Physics},

volume = {33},

number = {6},

pages = {2264-2264},

publisher = {AAPM},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Fichtinger2006,

title = {Robotically assisted prostate brachytherapy with transrectal ultrasound guidance–Phantom experiments},

author = {Gabor Fichtinger and E. Clif Burdette and Attila Tanacs and Alexandru Patriciu and Dumitru Mazilu and Louis L. Whitcomb and Dan Stoianovici},

url = {http://dx doi org/10 1016/j brachy 2005 10 003

https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Fichtinger2006.pdf},

doi = {10 1016/j brachy 2005 10 003},

year  = {2006},

date = {2006-01-01},

urldate = {2006-01-01},

journal = {Brachytherapy},

volume = {5},

number = {1},

pages = {14–26},

publisher = {Engineering Research Center, The Johns Hopkins University, Baltimore, MD 21218-2682, USA gabor@cs jhu edu},

abstract = {<p>PURPOSE: To report the preliminary experimental results obtained with a robot-assisted transrectal ultrasound (TRUS)-guided prostate brachytherapy system METHODS AND MATERIALS: The system consists of a TRUS unit, a spatially coregistered needle insertion robot, and an FDA-approved treatment planning, image-registered implant system The robot receives each entry/target coordinate pair of the implant plan, inserts a preloaded needle, and then the seeds are deposited The needles/sources are tracked in TRUS, thus allowing the plan to be updated as the procedure progresses RESULTS: The first insertion attempt was recorded for each needle, without adjustment All clinically relevant locations were reached in a prostate phantom Nonparallel, parallel needle trajectories were demonstrated Based on TRUS, the average transverse placement error was 2 mm (worst case 2 5 mm, 80% less than 2 mm), and the average sagittal error was 2 5 mm (worst case 5 0 mm, 70% less than 2 5 mm) CONCLUSIONS: The concept, technical viability of robot-assisted brachytherapy were demonstrated in phantoms The kinematically decoupled robotic assistant device is inherently safe Overall performance was promising, but further optimization is necessary to prove the possibility of improved dosimetry</p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Vikal2006a,

title = {Seed Segmentation in C-Arm Fluoroscopy for Brachytherapy Implant Reconstruction},

author = {Siddharth Vikal and Ameet K. Jain and Anton Degeut and Danny Y Song and Gabor Fichtinger},

url = {http://link aip org/link/?MPH/33/2229/2

https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Vikal2006a.pdf},

doi = {10 1118/1 2241679},

year  = {2006},

date = {2006-01-01},

urldate = {2006-01-01},

journal = {Journal of Medical Physics},

volume = {33},

number = {6},

pages = {2229-2229},

publisher = {AAPM},

keywords = {},

pubstate = {published},

tppubtype = {article}

}