@article {Rivaz2008b, title = {Ablation monitoring with elastography: 2D in-vivo and 3D ex-vivo studies}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {11}, number = {Pt 2}, year = {2008}, pages = {458{\textendash}466}, publisher = {ERC for Computer Integrated Surgery, Johns Hopkins University, USA rivaz@jhu edu}, abstract = {

The clinical feasibility of 2D elastography methods is hindered by the requirement that the operator avoid out-of-plane motion of the ultrasound image during palpation, and also by the lack of volumetric elastography measurements In this paper, we develop, evaluate a 3D elastography method operating on volumetric data acquired from a 3D probe Our method is based on minimizing a cost function using dynamic programming (DP) The cost function incorporates similarity of echo amplitudes, displacement continuity We present, to the best of our knowledge, the first in-vivo patient studies of monitoring liver ablation with freehand DP elastography The thermal lesion was not discernable in the B-mode image but it was clearly visible in the strain image as well as in validation CT We also present 3D strain images from thermal lesions in ex-vivo ablation Good agreement was observed between strain images, CT, gross pathology

}, keywords = {Carcinoma, Catheter Ablation, Computer-Assisted, Elasticity Imaging Techniques, Feasibility Studies, Hepatectomy, Hepatocellular, Humans, Image Interpretation, Imaging, Liver Neoplasms, methods, Surgery, surgery/ultrasonography, Three-Dimensional, Treatment Outcome}, author = {Hassan Rivaz and Ioana Fleming and Lia Assumpcao and Gabor Fichtinger and Ulrike Hamper and Michael Choti and Gregory D. Hager and Emad Boctor} } @article {Foroughi2008, title = {Localization of pelvic anatomical coordinate system using US/atlas registration for total hip replacement}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {11}, number = {Pt 2}, year = {2008}, pages = {871{\textendash}879}, publisher = {Johns Hopkins University, Baltimore, MD, USA pezhman@cs jhu edu}, abstract = {

In Total Hip Replacement (THR) procedures, misalignment of the acetabular component can lead to dislocation, impingement For the successful alignment of acetabular component, precise estimation of pelvic anatomical coordinate system is necessary Conventional navigation systems use CT scan or fluoroscopy, or involve implanted bone fiducials or invasive probing of bony landmarks to locate the anatomical coordinate In this paper, an ultrasound-based approach is proposed that exploits prior knowledge about the anatomy of the pelvis in the form of a 3D surface atlas Tracked ultrasound images are utilized to extract sample points from the surface of the pelvis A generic coordinate system in the specific patient is localized by registering these points to a statistical atlas of the pelvis in which a canonical anatomical coordinate system had been defined This technique has been evaluated using simulation, dry bone, and cadaver experiments, was able to localize the anatomical coordinate system with the accuracy of about 1 degree

}, keywords = {Algorithms, Arthroplasty, Automated, Computer-Assisted, Hip, Hip Joint, Humans, Image Enhancement, Image Interpretation, Imaging, methods, Pattern Recognition, Pelvic Bones, Replacement, Reproducibility of Results, Sensitivity, Specificity, Subtraction Technique, Surgery, surgery/ultrasonography, Three-Dimensional, Ultrasonography}, author = {Pezhman Foroughi and Danny Y Song and Gouthami Chintalapani and Russell H. Taylor and Gabor Fichtinger} } @conference {Karim-Aghaloo2008, title = {Towards detecting surgical clips in 3D ultrasound for target localization in radiation therapy: a study on tissue phantoms}, booktitle = {International Conference of the IEEE Engineering in Medicine and Biology Society}, volume = {2008}, year = {2008}, pages = {5282{\textendash}5285}, publisher = {Department of Electrical, Computer Engineering, Queens University, Kingston, ON K7L3N6, Canada}, organization = {Department of Electrical, Computer Engineering, Queens University, Kingston, ON K7L3N6, Canada}, abstract = {

A study is performed to measure the visibility of small surgical clips in 3D ultrasound volumes of a phantom as the first step towards using such clips as fiducial markers in radiation therapy Visibility is calculated as the contrast to noise ratio of the echo from the clip to the background The appearance of a resonance tail is also calculated using a moment analysis Contrast is found to be high, mostly independent of material, size of the clip All clips are visible, but the length of the tail is found to be dependent on clip orientation to the ultrasound beam The consistent visibility of the clips suggests they are suitable as fiducial markers in ultrasound, the dependency of the resonance tail on orientation provides an opportunity to distinguish clips from other specular reflectors

}, keywords = {Computer-Assisted, Equipment Design, Equipment Failure Analysis, Humans, Image Enhancement, Imaging, instrumentation, instrumentation/methods, methods, Phantoms, Radiotherapy, Reproducibility of Results, Sensitivity, Specificity, Surgical Instruments, Three-Dimensional, Ultrasonography}, doi = {10 1109/IEMBS 2008 4650406}, url = {http://dx doi org/10 1109/IEMBS 2008 4650406}, author = {Zahra Karim-Aghaloo and Prasad Shrawane and Purang Abolmaesumi and Gabor Fichtinger and Robert Rohling} } @article {Rivaz2008a, title = {Ultrasound elastography: a dynamic programming approach}, journal = {IEEE transactions on medical imaging}, volume = {27}, number = {10}, year = {2008}, month = {Oct}, pages = {1373{\textendash}1377}, publisher = {Engineering Research Center for Computer Integrated Surgery, Johns Hopkins University, 3400 N Charles Street, Baltimore, MD 21218, USA}, abstract = {

This paper introduces a 2-D strain imaging technique based on minimizing a cost function using dynamic programming (DP) The cost function incorporates similarity of echo amplitudes, displacement continuity Since tissue deformations are smooth, the incorporation of the smoothness into the cost function results in reduced decorrelation noise As a result, the method generates high-quality strain images of freehand palpation elastography with up to 10\% compression, showing that the method is more robust to signal decorrelation (caused by scatterer motion in high axial compression, nonaxial motions of the probe) in comparison to the standard correlation techniques The method operates in less than 1 s, is thus also potentially suitable for real time elastography

}, keywords = {Algorithms, Computer-Assisted, Elasticity Imaging Techniques, Humans, Image Enhancement, Image Interpretation, Imaging, instrumentation/methods, methods, Numerical Analysis, Phantoms, Sensitivity, Specificity}, doi = {10 1109/TMI 2008 917243}, url = {http://dx doi org/10 1109/TMI 2008 917243}, author = {Hassan Rivaz and Emad Boctor and Pezhman Foroughi and Richard Zellars and Gabor Fichtinger and Gregory D. Hager} } @article {Krieger2007a, title = {Design and preliminary accuracy studies of an MRI-guided transrectal prostate intervention system}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {10}, number = {Pt 2}, year = {2007}, pages = {59{\textendash}67}, publisher = {Department of Mechanical Engineering, Johns Hopkins University, Baltimore, USA}, abstract = {

This paper reports a novel system for magnetic resonance imaging (MRI) guided transrectal prostate interventions, such as needle biopsy, fiducial marker placement, and therapy delivery The system utilizes a hybrid tracking method, comprised of passive fiducial tracking for initial registration, subsequent incremental motion measurement along the degrees of freedom using fiber-optical encoders, mechanical scales Targeting accuracy of the system is evaluated in prostate phantom experiments Achieved targeting accuracy, procedure times were found to compare favorably with existing systems using passive, active tracking methods Moreover, the portable design of the system using only standard MRI image sequences, minimal custom scanner interfacing allows the system to be easily used on different MRI scanners

}, keywords = {Algorithms, Artificial Intelligence, Automated, Biopsy, Computer-Assisted, Equipment Design, Equipment Failure Analysis, Humans, Image Enhancement, Image Interpretation, Imaging, instrumentation/methods, Interventional, Magnetic Resonance Imaging, Male, methods, Needle, pathology/surgery, Pattern Recognition, Pilot Projects, Prostatectomy, Prostatic Neoplasms, Rectum, Reproducibility of Results, Robotics, Sensitivity, Specificity, Three-Dimensional, User-Computer Interface}, author = {Axel Krieger and Csaba Csoma and Iulian Iordachita and Peter Guion and Anurag K. Singh and Gabor Fichtinger and Whitcomb, Louis L.} } @article {Kazanzides2007, title = {Development of an image-guided robot for small animal research}, journal = {Journal of Computer Aided Surgery}, volume = {12}, number = {6}, year = {2007}, month = {Nov}, pages = {357{\textendash}365}, publisher = {Department of Computer Science, The Johns Hopkins University, Baltimore, Maryland 21218, USA pkaz@jhu edu}, abstract = {

We developed a robot system that can be used for image-guided experimental procedures on small animals, where the goal is to perform physical actions at specific positions identified on a preoperative image The animal is first placed in a fixture that is compatible with all imaging systems of interest, including PET, SPECT, CT, MRI After imaging, the fixture is attached, registered to the robot system, where the image-guided intervention is performed This system has been applied to perform pO(2) measurements with physical probes based on tumor hypoxia images obtained in an animal PET scanner This paper focuses on the design, validation of the robot system The validation is performed using a phantom, includes a new method for estimating the Fiducial Localization Error (FLE) that is based on the measured Fiducial Distance Error (FDE) The results indicate that the robot system can position the measurement probe at a defined target with a mean error that is less than 0 4 mm

}, keywords = {Algorithms, analysis, Animals, Imaging, Laboratory, methods, Oxygen, Partial Pressure, Phantoms, Positron-Emission Tomography, Robotics}, doi = {10 1080/10929080701732538}, url = {http://dx doi org/10 1080/10929080701732538}, author = {Peter Kazanzides and Jenghwa Chang and Iulian Iordachita and Jack Li and Clifton Ling and Gabor Fichtinger} } @article {DiMaio2007, title = {Dynamic MRI scan plane control for passive tracking of instruments and devices}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {10}, number = {Pt 2}, year = {2007}, pages = {50{\textendash}58}, publisher = {Brigham, Women{\textquoteright}s Hospital, Harvard Medical School, Boston, MA, USA}, abstract = {

This paper describes a novel image-based method for tracking robotic mechanisms, interventional devices during Magnetic Resonance Image (MRI)-guided procedures It takes advantage of the multi-planar imaging capabilities of MRI to optimally image a set of localizing fiducials for passive motion tracking in the image coordinate frame The imaging system is servoed to adaptively position the scan plane based on automatic detection, localization of fiducial artifacts directly from the acquired image stream This closed-loop control system has been implemented using an open-source software framework, currently operates with GE MRI scanners Accuracy, performance were evaluated in experiments, the results of which are presented here

}, keywords = {Algorithms, Anatomy, Artificial Intelligence, Automated, Computer-Assisted, Cross-Sectional, Humans, Image Enhancement, Image Interpretation, Imaging, instrumentation/methods, Magnetic Resonance Imaging, methods, Pattern Recognition, Phantoms, Reproducibility of Results, Robotics, Sensitivity, Specificity, Surgery, Three-Dimensional, User-Computer Interface}, author = {Simon DiMaio and Eigil Samset and Gregory Fischer and Iulian Iordachita and Gabor Fichtinger and Ferenc Jolesz and Clare M Tempany} } @article {Jain2007, title = {Intra-operative 3D guidance in prostate brachytherapy using a non-isocentric C-arm}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {10}, number = {Pt 2}, year = {2007}, pages = {9{\textendash}17}, publisher = {Johns Hopkins University, USA}, abstract = {

Intra-operative guidance in Transrectal Ultrasound (TRUS) guided prostate brachytherapy requires localization of inserted radioactive seeds relative to the prostate Seeds were reconstructed using a typical C-arm, and exported to a commercial brachytherapy system for dosimetry analysis Technical obstacles for 3D reconstruction on a non-isocentric C-arm included pose-dependent C-arm calibration; distortion correction; pose estimation of C-arm images; seed reconstruction;, C-arm to TRUS registration In precision-machined hard phantoms with 40-100 seeds, we correctly reconstructed 99 8\% seeds with a mean 3D accuracy of 0 68 mm In soft tissue phantoms with 45-87 seeds, clinically realistic 15 degrees C-arm motion, we correctly reconstructed 100\% seeds with an accuracy of 1 3 mm The reconstructed 3D seed positions were then registered to the prostate segmented from TRUS In a Phase-1 clinical trial, so far on 4 patients with 66-84 seeds, we achieved intra-operative monitoring of seed distribution, dosimetry We optimized the 100\% prescribed iso-dose contour by inserting an average of 3 75 additional seeds, making intra-operative dosimetry possible on a typical C-arm, at negligible additional cost to the existing clinical installation

}, keywords = {Algorithms, Brachytherapy, Computer-Assisted, Equipment Design, Equipment Failure Analysis, Humans, Imaging, instrumentation/methods, Interventional, Intraoperative Care, Male, methods, Prostatic Neoplasms, Prosthesis Implantation, Radiographic Image Enhancement, Radiographic Image Interpretation, Radiography, radiography/radiotherapy, Radiotherapy, Reproducibility of Results, Sensitivity, Specificity, Three-Dimensional, Tomography, X-Ray Computed}, author = {Ameet K. Jain and Anton Degeut and Iulian Iordachita and Gouthami Chintalapani and Jack Blevins and Le Yi and Elwood Armour and E. Clif Burdette and Danny Y Song and Gabor Fichtinger} } @article {Liu2007, title = {Prostate implant reconstruction with discrete tomography}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {10}, number = {Pt 1}, year = {2007}, pages = {734{\textendash}742}, publisher = {Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA}, abstract = {

We developed a discrete tomography method for prostate implant reconstructions using only a limited number of X-ray projection images A 3D voxel volume is reconstructed by back-projection, using distance maps generated from the projection images The true seed locations are extracted from the voxel volume while false positive seeds are eliminated using a novel optimal geometry coverage model The attractive feature of our method is that it does not require exact seed segmentation of the X-ray images, it yields near 100\% correct reconstruction from only six images with an average reconstruction accuracy of 0 86 mm (std = 0 46mm)

}, keywords = {Brachytherapy, Computer-Assisted, Humans, Imaging, instrumentation/methods, Male, methods, Prostatic Neoplasms, Prosthesis Implantation, Radiographic Image Enhancement, Radiographic Image Interpretation, radiography/radiotherapy, Three-Dimensional}, author = {Xiaofeng Liu and Ameet K. Jain and Gabor Fichtinger} } @article {Krupa2007, title = {Real-time tissue tracking with B-mode ultrasound using speckle and visual servoing}, journal = {Tenth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)}, volume = {10}, number = {Pt 2}, year = {2007}, pages = {1{\textendash}8}, publisher = {IRISA - INRIA Rennes, France alexandre krupa@irisa fr}, abstract = {

We present a method for real-time tracking of moving soft tissue with B-mode ultrasound (US) The method makes use of the speckle information contained in the US images to estimate the in-plane, out-of-plane motion of a fixed target relative to the ultrasound scan plane The motion information is then used as closed-loop feedback to a robot which corrects for the target motion The concept is demonstrated for translation motions in an experimental setup consisting of an ultrasound speckle phantom, a robot for simulating tissue motion, and a robot that performs motion stabilization from US images This concept shows promise for US-guided procedures that require real-time motion tracking, compensation

}, keywords = {Algorithms, Artificial Intelligence, Computer Systems, Computer-Assisted, Equipment Design, Equipment Failure Analysis, Image Enhancement, Image Interpretation, Imaging, instrumentation/methods, Interventional, methods, Pilot Projects, Reproducibility of Results, Robotics, Sensitivity, Specificity, Surgery, Three-Dimensional, Ultrasonography, User-Computer Interface}, author = {Alexandre Krupa and Gabor Fichtinger and Gregory D. Hager} } @article {Labat2007, title = {Toward optimal matching for 3D reconstruction of brachytherapy seeds}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {10}, number = {Pt 2}, year = {2007}, pages = {701{\textendash}709}, publisher = {Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA}, abstract = {

X-ray C-arm fluoroscopy is a natural choice for intra-operative seed localization in prostate brachytherapy Resolving the correspondence of seeds in the projection images can be modeled as an assignment problem that is NP-hard Our approach rests on the practical observation that the optimal solution has almost zero cost if the pose of the C-arm is known accurately This allowed us to to derive an equivalent problem of reduced dimensionality that, with linear programming, can be solved efficiently in polynomial time Additionally, our method demonstrates significantly increased robustness to C-arm pose errors when compared to the prior art Because under actual clinical circumstances it is exceedingly difficult to track the C-arm, easing on this constraint has additional practical utility

}, keywords = {Algorithms, Artificial Intelligence, Automated, Brachytherapy, Computer-Assisted, Image Enhancement, Image Interpretation, Imaging, instrumentation/methods, methods, Pattern Recognition, Phantoms, Prosthesis Implantation, Radiotherapy, Reproducibility of Results, Sensitivity, Specificity, Three-Dimensional, Tomography, X-Ray Computed}, author = {Christian Labat and Ameet K. Jain and Gabor Fichtinger and Jerry L. Prince} } @article {Blumenfeld2007, title = {Transperineal prostate biopsy under magnetic resonance image guidance: a needle placement accuracy study}, journal = {Journal of magnetic resonance imaging}, volume = {26}, number = {3}, year = {2007}, month = {Sep}, pages = {688{\textendash}694}, publisher = {Department of Radiology, Brigham, Women{\textquoteright}s Hospital, Harvard Medical School, Boston, Massachusetts, USA}, abstract = {

PURPOSE: To quantify needle placement accuracy of magnetic resonance image (MRI)-guided core needle biopsy of the prostate MATERIALS AND METHODS: A total of 10 biopsies were performed with 18-gauge (G) core biopsy needle via a percutaneous transperineal approach Needle placement error was assessed by comparing the coordinates of preplanned targets with the needle tip measured from the intraprocedural coherent gradient echo images The source of these errors was subsequently investigated by measuring displacement caused by needle deflection, needle susceptibility artifact shift in controlled phantom studies Needle placement error due to misalignment of the needle template guide was also evaluated RESULTS: The mean, standard deviation (SD) of errors in targeted biopsies was 6 5 +/- 3 5 mm Phantom experiments showed significant placement error due to needle deflection with a needle with an asymmetrically beveled tip (3 2-8 7 mm depending on tissue type) but significantly smaller error with a symmetrical bevel (0 6-1 1 mm) Needle susceptibility artifacts observed a shift of 1 6 +/- 0 4 mm from the true needle axis Misalignment of the needle template guide contributed an error of 1 5 +/- 0 3 mm CONCLUSION: Needle placement error was clinically significant in MRI-guided biopsy for diagnosis of prostate cancer Needle placement error due to needle deflection was the most significant cause of error, especially for needles with an asymmetrical bevel

}, keywords = {Aged, Artifacts, Biopsy, Contrast Media, diagnosis/pathology, Humans, Imaging, Magnetic Resonance Imaging, Magnetic Resonance Spectroscopy, Male, methods, Middle Aged, Needle, Needles, Phantoms, pharmacology, Prostatectomy, Prostatic Neoplasms, Reproducibility of Results, Retrospective Studies}, doi = {10 1002/jmri 21067}, url = {http://dx doi org/10 1002/jmri 21067}, author = {Philip Blumenfeld and Nobuhiko Hata and Simon DiMaio and Kelly Zou and Steven Haker and Gabor Fichtinger and Clare M Tempany} } @article {Boctor2006a, title = {Bootstrapped ultrasound calibration}, journal = {Studies in health technology and informatics}, volume = {119}, year = {2006}, pages = {61{\textendash}66}, publisher = {Engineering Research Center, Johns Hopkins University, USA}, abstract = {

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

}, keywords = {Calibration, Imaging, standards, Three-Dimensional, Ultrasonography, United States}, author = {Emad Boctor and Iulian Iordachita and Michael Choti and Gregory D. Hager and Gabor Fichtinger} } @article {Jain2006a, title = {C-arm tracking and reconstruction without an external tracker}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {9}, number = {Pt 1}, year = {2006}, pages = {494{\textendash}502}, publisher = {Department of Computer Science, Johns Hopkins University, USA}, abstract = {

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

}, keywords = {Algorithms, Calibration, Computer-Assisted, Equipment Design, Equipment Failure Analysis, Fluoroscopy, Imaging, instrumentation/methods, methods, Radiographic Image Enhancement, Radiographic Image Interpretation, Reproducibility of Results, Sensitivity, Specificity, Three-Dimensional}, author = {Ameet K. Jain and Gabor Fichtinger} } @article {Kazanzides2006, title = {Design, validation of an image-guided robot for small animal research}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {9}, number = {Pt 1}, year = {2006}, pages = {50{\textendash}57}, publisher = {Department of Computer Science, Johns Hopkins University, USA pkaz@jhu edu}, abstract = {

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)

}, keywords = {Animals, Biopsy, Computer-Assisted, Equipment Design, Equipment Failure Analysis, Imaging, Injections, instrumentation/methods, instrumentation/methods/veterinary, Needle, Phantoms, Positron-Emission Tomography, Research, Robotics, Surgery}, author = {Peter Kazanzides and Jenghwa Chang and Iulian Iordachita and Jack Li and Clifton Ling and Gabor Fichtinger} } @article {Xu2006a, title = {Lung deformation estimation and four-dimensional CT lung reconstruction}, journal = {Journal of Academic Radiology}, volume = {13}, number = {9}, year = {2006}, month = {Sep}, pages = {1082{\textendash}1092}, publisher = {Philips Research North America, 345 Scarborough Road, Briarcliff Manor, NY 10510, USA sheng xu@philips com}, abstract = {

RATIONALE AND OBJECTIVES: Four-dimensional (4D) computed tomography (CT) can be used in radiation treatment planning to account for respiratory motion Current 4D CT techniques have limitations in either spatial or temporal resolution In addition, most of these techniques rely on auxiliary surrogates to relate the time of the CT scan to the patient{\textquoteright}s respiratory phase We propose a 4D CT method for lung applications to overcome these problems MATERIALS AND METHODS: A set of axial scans are taken at multiple table positions to obtain a series of two-dimensional images while the patient is breathing freely Each two-dimensional image is registered to a reference CT volume The deformation of the image with respect to the volume is used to synchronize the image with the respiratory cycle assuming that there is no phase variation along the craniocaudal direction The reconstructed 4D dataset is a series of deformable transformations of the reference volume RESULTS: A synthetic 4D dataset showed that the registration error is less than 5\% of the image deformation A swine study showed that the algorithm can generate better image quality than the image sorting method A respiratory-gated 4D dataset showed that the algorithm{\textquoteright}s result is consistent with the ground truth CONCLUSION: The algorithm can reconstruct good quality 4D images without external surrogates even if the CT scans are acquired under irregular respiratory motion The algorithm may allow for reduced radiation dose to the patient with a limited loss of image quality Although the phase variation exists along the craniocaudal direction, the 4D reconstruction is reasonably accurate

}, keywords = {Algorithms, Artifacts, Computer-Assisted, Humans, Imaging, Information Storage, Lung, methods, Movement, Phantoms, Radiographic Image Enhancement, Radiographic Image Interpretation, Radiography, Reproducibility of Results, Respiratory Mechanics, Retrieval, Sensitivity, Specificity, Three-Dimensional, Tomography, X-Ray Computed}, doi = {10 1016/j acra 2006 05 004}, url = {http://dx doi org/10 1016/j acra 2006 05 004}, author = {Sheng Xu and Russell H. Taylor and Gabor Fichtinger and Kevin Cleary} } @article {Boctor2006b, title = {Ultrasound monitoring of tissue ablation via deformation model and shape priors}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {9}, number = {Pt 2}, year = {2006}, pages = {405{\textendash}412}, abstract = {

A rapid approach to monitor ablative therapy through optimizing shape, elasticity parameters is introduced Our motivating clinical application is targeting, intraoperative monitoring of hepatic tumor thermal ablation, but the method translates to the generic problem of encapsulated stiff masses (solid organs, tumors, ablated lesions, etc ) in ultrasound imaging The approach involves the integration of the following components: a biomechanical computational model of the tissue, a correlation approach to estimate/track tissue deformation, and an optimization method to solve the inverse problem, recover the shape parameters in the volume of interest Successful convergence, reliability studies were conducted on simulated data Then ex-vivo studies were performed on 18 ex-vivo bovine liver samples previously ablated under ultrasound monitoring in controlled laboratory environment While B-mode ultrasound does not clearly identify the development of necrotic lesions, the proposed technique can potentially segment the ablation zone The same framework can also yield both partial, full elasticity reconstruction

}, keywords = {Algorithms, Animals, Automated, Biological, Cattle, Computer-Assisted, Elasticity, Hepatectomy, Image Enhancement, Image Interpretation, Imaging, Interventional, Liver, Mechanical, methods, Models, Pattern Recognition, physiology/surgery/ultrasonography, Reproducibility of Results, Sensitivity, Specificity, Statistical, Stress, Subtraction Technique, Surgery, Three-Dimensional, Ultrasonography}, author = {Emad Boctor and Michelle de Oliveira and Michael Choti and Roger Ghanem and Russell H. Taylor and Gregory D. Hager and Gabor Fichtinger} } @article {Jain2005, title = {C-arm calibration-is it really necessary?}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {8}, number = {Pt 1}, year = {2005}, pages = {639{\textendash}646}, abstract = {

C-arm fluoroscopy is modelled as a perspective projection, the parameters of which are estimated through a calibration procedure It has been universally accepted that precise intra-procedural calibration is a prerequisite for accurate quantitative C-arm fluoroscopy guidance Calibration, however, significantly adds to system complexity, which is a major impediment to clinical practice We challenge the status quo by questioning the assumption that precise intra-procedural calibration is really necessary We derived theoretical bounds for the sensitivity of 3D measurements to mis-calibration Experimental results corroborated the theory in that mis-calibration in the focal spot by as much as 50 mm still allows for tracking with an accuracy of 0 5 mm in translation, 0 65 degrees in rotation, and such mis-calibration does not impose any additional error on the reconstruction of small objects

}, keywords = {Algorithms, Calibration, Computer-Assisted, Equipment Failure Analysis, Fluoroscopy, Imaging, instrumentation/methods/standards, methods/standards, Radiographic Image Enhancement, Radiographic Image Interpretation, Reproducibility of Results, Sensitivity, Specificity, Three-Dimensional, United States}, author = {Ameet K. Jain and Ryan Kon and Yu Zhou and Gabor Fichtinger} } @article {Krieger2005a, title = {Design of a novel MRI compatible manipulator for image guided prostate interventions}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {52}, number = {2}, year = {2005}, month = {Feb}, pages = {306{\textendash}313}, abstract = {

This paper reports a novel remotely actuated manipulator for access to prostate tissue under magnetic resonance imaging guidance (APT-MRI) device, designed for use in a standard high-field MRI scanner The device provides three-dimensional MRI guided needle placement with millimeter accuracy under physician control Procedures enabled by this device include MRI guided needle biopsy, fiducial marker placements, and therapy delivery Its compact size allows for use in both standard cylindrical, open configuration MRI scanners Preliminary in vivo canine experiments, first clinical trials are reported

}, keywords = {Animals, Biopsy, Computer-Assisted, Dogs, Equipment Design, Equipment Failure Analysis, Feasibility Studies, Imaging, instrumentation/methods, Magnetic Resonance Imaging, Male, Micromanipulation, Needle, pathology/surgery, Prostate, Reproducibility of Results, Robotics, Sensitivity, Specificity, Surgery, Three-Dimensional}, doi = {10 1109/TBME 2004 840497}, url = {http://dx doi org/10 1109/TBME 2004 840497}, author = {Axel Krieger and Robert Susil and Cynthia Menard and Jonathan Coleman and Gabor Fichtinger and Ergin Atalar and Whitcomb, Louis L.} } @article {Jain2005a, title = {FTRAC}, journal = {Journal of Medical Physics}, volume = {32}, number = {10}, year = {2005}, month = {Oct}, pages = {3185{\textendash}3198}, abstract = {

C-arm fluoroscopy is ubiquitous in contemporary surgery, but it lacks the ability to accurately reconstruct three-dimensional (3D) information A major obstacle in fluoroscopic reconstruction is discerning the pose of the x-ray image, in 3D space Optical/magnetic trackers tend to be prohibitively expensive, intrusive, cumbersome in many applications We present single-image-based fluoroscope tracking (FTRAC) with the use of an external radiographic fiducial consisting of a mathematically optimized set of ellipses, lines, and points This is an improvement over contemporary fiducials, which use only points The fiducial encodes six degrees of freedom in a single image by creating a unique view from any direction A nonlinear optimizer can rapidly compute the pose of the fiducial using this image The current embodiment has salient attributes: small dimensions (3 x 3 x 5 cm); need not be close to the anatomy of interest;, accurately segmentable We tested the fiducial, the pose recovery method on synthetic data, also experimentally on a precisely machined mechanical phantom Pose recovery in phantom experiments had an accuracy of 0 56 mm in translation, 0 33 degrees in orientation Object reconstruction had a mean error of 0 53 mm with 0 16 mm STD The method offers accuracies similar to commercial tracking systems, and appears to be sufficiently robust for intraoperative quantitative C-arm fluoroscopy Simulation experiments indicate that the size can be further reduced to 1 x 1 X 2 cm, with only a marginal drop in accuracy

}, keywords = {Algorithms, Computer-Assisted, Fluoroscopy, Imaging, Information Storage, instrumentation/methods, methods, Phantoms, Radiographic Image Enhancement, Radiographic Image Interpretation, Reproducibility of Results, Retrieval, Sensitivity, Specificity, Three-Dimensional}, author = {Ameet K. Jain and Tabish Mustufa and Yu Zhou and E. Clif Burdette and Gregory Chirikjian and Gabor Fichtinger} } @article {Fichtinger2005, title = {Image overlay for CT-guided needle insertions}, journal = {Journal of Computer Aided Surgery}, volume = {10}, number = {4}, year = {2005}, month = {Jul}, pages = {241{\textendash}255}, abstract = {

OBJECTIVE: We present a 2D image overlay device to assist needle placement on computed tomography (CT) scanners MATERIALS AND METHODS: The system consists of a flat display, a semitransparent mirror mounted on the gantry When the physician looks at the patient through the mirror, the CT image appears to be floating inside the body with correct size, position as if the physician had 2D {\textquoteright}X-ray vision{\textquoteright} The physician draws the optimal path on the CT image The composite image is rendered on the display, thus reflected in the mirror The reflected image is used to guide the physician in the procedure In this article, we describe the design, various embodiments of the 2D image overlay system, followed by the results of phantom, cadaver experiments in multiple clinical applications RESULTS: Multiple skeletal targets were successfully accessed with one insertion attempt Generally, successful access was recorded on liver targets when a clear path opened, but the number of attempts, accuracy showed variability because of occasional lack of access Soft tissue deformation further reduced the accuracy, consistency in comparison to skeletal targets CONCLUSION: The system demonstrated strong potential for reducing faulty needle insertion attempts, thereby reducing X-ray dose, patient discomfort

}, keywords = {Animals, Biopsy, Cadaver, Calibration, Computer-Assisted, Equipment Design, Humans, Image Processing, Imaging, instrumentation, Interventional, Needle, Phantoms, Radiography, Swine, Tomography, User-Computer Interface, X-Ray Computed}, doi = {10 1080/10929080500230486}, url = {http://dx doi org/10 1080/10929080500230486}, author = {Gabor Fichtinger and Anton Degeut and Gregory Fischer and Iulian Iordachita and Emese Balogh and Ken Masamune and Russell H. Taylor and Laura Fayad and Michelle de Oliveira and James Zinreich} } @article {Xu2005b, title = {Lung deformation estimation and four-dimensional CT lung reconstruction}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {8}, number = {Pt 2}, year = {2005}, pages = {312{\textendash}319}, abstract = {

Four-dimensional (4D) computed tomography (CT) image acquisition is a useful technique in radiation treatment planning, interventional radiology in that it can account for respiratory motion of lungs Current 4D lung reconstruction techniques have limitations in either spatial or temporal resolution In addition, most of these techniques rely on auxiliary surrogates to relate the time of CT scan to the patient{\textquoteright}s respiratory phase In this paper, we propose a novel 4D CT lung reconstruction, deformation estimation algorithm Our algorithm is purely image based The algorithm can reconstruct high quality 4D images even if the original images are acquired under irregular respiratory motion The algorithm is validated using synthetic 4D lung data Experimental results from a swine study data are also presented

}, keywords = {Algorithms, Animals, Artificial Intelligence, Biological, Computer Simulation, Computer-Assisted, Elasticity, Humans, Imaging, Lung, methods, Models, physiology/radiography, Radiographic Image Enhancement, Radiographic Image Interpretation, Reproducibility of Results, Respiratory Mechanics, Sensitivity, Specificity, Swine, Three-Dimensional, Tomography, X-Ray Computed}, author = {Sheng Xu and Russell H. Taylor and Gabor Fichtinger and Kevin Cleary} } @article {Jain2005e, title = {Matching and reconstruction of brachytherapy seeds using the Hungarian algorithm (MARSHAL)}, journal = {Journal of Medical Physics}, volume = {32}, number = {11}, year = {2005}, month = {Nov}, pages = {3475{\textendash}3492}, abstract = {

Intraoperative dosimetric quality assurance in prostate brachytherapy critically depends on discerning the three-dimensional (3D) locations of implanted seeds The ability to reconstruct the implanted seeds intraoperatively will allow us to make immediate provisions for dosimetric deviations from the optimal implant plan A method for seed reconstruction from segmented C-arm fluoroscopy images is proposed The 3D coordinates of the implanted seeds can be calculated upon resolving the correspondence of seeds in multiple x-ray images We formalize seed-matching as a combinatorial optimization problem, which has salient features: (a) extensively studied solutions by the computer science community; (b) proof for the nonexistence of any polynomial time exact algorithm;, (c) a practical pseudo-polynomial algorithm that mostly runs in O(N3) time using any number of images We prove that two images are insufficient to correctly match the seeds, while a third image renders the matching problem to be of nonpolynomial complexity We utilize the special structure of the problem, propose a pseudopolynomial time algorithm Using three presegmented images, matching, reconstruction of brachytherapy seeds using the Hungarian algorithm achieved complete matching in simulation experiments;, 98 5\% in phantom experiments 3D reconstruction error for correctly matched seeds has a mean of 0 63 mm, and 0 9 mm for incorrectly matched seeds The maximum seed reconstruction error in each implant was typically around 1 32 mm Both on synthetic data, in phantom experiments, matching rate, reconstruction error achieved using presegmented images was found to be sufficient for prostate brachytherapy The algorithm is extendable to deal with arbitrary number of images without any loss in speed or accuracy The algorithm is sufficiently generic to provide a practical solution to any correspondence problem, across different imaging modalities, features

}, keywords = {Algorithms, Automated, Brachytherapy, Calibration, Computer Simulation, Computer-Assisted, Humans, Image Interpretation, Imaging, Male, methods, Models, Numerical Analysis, Pattern Recognition, Phantoms, Prostatic Neoplasms, Radiographic Image Enhancement, Radiographic Image Interpretation, Radiometry, Radiotherapy, Radiotherapy Dosage, Radiotherapy Planning, Reproducibility of Results, Statistical, Theoretical, Three-Dimensional, Time Factors, Ultrasonography}, author = {Ameet K. Jain and Yu Zhou and Tabish Mustufa and E. Clif Burdette and Gregory Chirikjian and Gabor Fichtinger} } @article {Cleary2005, title = {Precision placement of instruments for minimally invasive procedures using a "needle driver" robot}, journal = {international journal of medical robotics computer assisted surgery MRCAS}, volume = {1}, number = {2}, year = {2005}, month = {Jan}, pages = {40{\textendash}47}, abstract = {

Medical practice continues to move toward less invasive procedures Many of these procedures require the precision placement of a needle in the anatomy Over the past several years, our research team has been investigating the use of a robotic needle driver to assist the physician in this task This paper summarizes our work in this area The robotic system is briefly described, followed by a description of a clinical trial in spinal nerve blockade The robot was used under joystick control to place a 22 gauge needle in the spines of 10 patients using fluoroscopic imaging The results were equivalent to the current manual procedure We next describe our follow-up clinical application in lung biopsy for lung cancer screening under CT fluoroscopy The system concept is discussed, the results of a phantom study are presented A start-up company named ImageGuide has recently been formed to commercialize the robot Their revised robot design is presented, along with plans to install a ceiling-mounted version of the robot in the CT fluoroscopy suite at Georgetown University

}, keywords = {Biopsy, Cadaver, Equipment Design, Fluoroscopy, Humans, Imaging, instrumentation, instrumentation/methods, Lung, Lung Neoplasms, methods, Minimally Invasive, Needles, Nerve Block, pathology, pathology/radiography, Phantoms, Randomized Controlled Trials as Topic, Robotics, Spinal Nerves, Surgical Procedures, Tomography, X-Ray Computed}, doi = {10 1002/rcs 40}, url = {http://dx doi org/10 1002/rcs 40}, author = {Kevin Cleary and Vance Watson and David Lindisch and Russell H. Taylor and Gabor Fichtinger and Sheng Xu and Charles White and John Donlon and Michael Taylor and Alexandru Patriciu and Dumitru Mazilu and Dan Stoianovici} } @article {Shen2004a, title = {Optimized prostate biopsy via a statistical atlas of cancer spatial distribution}, journal = {Medical image analysis}, volume = {8}, number = {2}, year = {2004}, month = {Jun}, pages = {139{\textendash}150}, abstract = {

A methodology is presented for constructing a statistical atlas of spatial distribution of prostate cancer from a large patient cohort, and it is used for optimizing needle biopsy An adaptive-focus deformable model is used for the spatial normalization, registration of 100 prostate histological samples, which were provided by the Center for Prostate Disease Research of the US Department of Defense, resulting in a statistical atlas of spatial distribution of prostate cancer Based on this atlas, a statistical predictive model was developed to optimize the needle biopsy sites, by maximizing the probability of detecting cancer Experimental results using cross-validation show that the proposed method can detect cancer with a 99\% success rate using seven needles, in these samples

}, keywords = {Algorithms, Biological, Biopsy, Cohort Studies, Computer Simulation, Computer-Assisted, Forecasting, Humans, Image Processing, Imaging, Male, Models, Needle, pathology, Probability, Prostate, Prostatic Neoplasms, Reproducibility of Results, Statistical, statistics /\&/ numerical data, Three-Dimensional}, doi = {10 1016/j media 2003 11 002}, url = {http://dx doi org/10 1016/j media 2003 11 002}, author = {Dinggang Shen and Zhiqiang Lao and Jianchao Zeng and Wei Zhang and Isabel Sesterhenn and Leon Sun and Judd Moul and Edward Herskovits and Gabor Fichtinger and Christos Davatzikos} } @article {Boctor2003b, title = {Virtual remote center of motion control for needle placement robots}, journal = {Journal of Computer Aided Surgery}, volume = {9}, number = {5}, year = {2003}, pages = {175{\textendash}183}, abstract = {

OBJECTIVE: We present an algorithm that enables percutaneous needle-placement procedures to be performed with unencoded, unregistered, minimally calibrated robots while removing the constraint of placing the needle tip on a mechanically enforced Remote Center of Motion (RCM) MATERIALS AND METHODS: The algorithm requires only online tracking of the surgical tool, a five-degree-of-freedom (5-DOF) robot comprising three prismatic DOF, two rotational DOF An incremental adaptive motion control cycle guides the needle to the insertion point, also orients it to align with the target-entry-point line The robot executes RCM motion without having a physically constrained fulcrum point RESULTS: The proof-of-concept prototype system achieved 0 78 mm translation accuracy, 1 4 degrees rotational accuracy (this is within the tracker accuracy) within 17 iterative steps (0 5-1 s) CONCLUSION: This research enables robotic assistant systems for image-guided percutaneous procedures to be prototyped/constructed more quickly, less expensively than has been previously possible Since the clinical utility of such systems is clear, has been demonstrated in the literature, our work may help promote widespread clinical adoption of this technology by lowering system cost, complexity

}, keywords = {Algorithms, Computer-Assisted, Equipment Design, Imaging, instrumentation, Needles, Robotics, Surgery, Three-Dimensional}, doi = {10 1080/10929080500097661}, url = {http://dx doi org/10 1080/10929080500097661}, author = {Emad Boctor and Robert Webster and Herve Mathieu and Allison Okamura and Gabor Fichtinger} } @article {Lee2002, title = {Numerical algorithms for spatial registration of line fiducials from cross-sectional images}, journal = {Journal of Medical Physics}, volume = {29}, number = {8}, year = {2002}, month = {Aug}, pages = {1881{\textendash}1891}, abstract = {

We present several numerical algorithms for six-degree-of-freedom rigid-body registration of line fiducial objects to their marks in cross-sectional planar images, such as those obtained in CT, MRI, given the correspondence between the marks, line fiducials The area of immediate application is frame-based stereotactic procedures, such as radiosurgery, functional neurosurgery The algorithms are also suitable to problems where the fiducial pattern moves inside the imager, as is the case in robot-assisted image-guided surgical applications We demonstrate the numerical methods on clinical CT images, computer-generated data, compare their performance in terms of robustness to missing data, robustness to noise, and speed The methods show two unique strengths: (1) They provide reliable registration of incomplete fiducial patterns when up to two-thirds of the total fiducials are missing from the image;, (2) they are applicable to an arbitrary combination of line fiducials without algorithmic modification The average speed of the fastest algorithm is 0 3236 s for six fiducial lines in real CT data in a Matlab implementation

}, keywords = {Algorithms, Anatomy, anatomy /\&/ histology/radiography, Cross-Sectional, Head, Humans, Image Enhancement, Imaging, Magnetic Resonance Imaging, methods, Quality Control, Reproducibility of Results, Sensitivity, Specificity, Stereotaxic Techniques, Stochastic Processes, Subtraction Technique, Three-Dimensional, Tomography, X-Ray Computed}, author = {Sangyoon Lee and Gabor Fichtinger and Gregory Chirikjian} } @article {Masamune2001, title = {System for robotically assisted percutaneous procedures with computed tomography guidance}, journal = {Journal of Computer Aided Surgery}, volume = {6}, number = {6}, year = {2001}, pages = {370{\textendash}383}, abstract = {

We present the prototype of an image-guided robotic system for accurate, consistent placement of percutaneous needles in soft-tissue targets under CT guidance inside the gantry of a CT scanner The couch-mounted system consists of a seven-degrees-of-freedom passive mounting arm, a remote center-of-motion robot, and a motorized needle-insertion device Single-image-based coregistration of the robot, image space is achieved by stereotactic localization using a miniature version of the BRW head frame built into the radiolucent needle driver The surgeon plans, controls the intervention in the scanner room on a desktop computer that receives DICOM images from the scanner The system does not need calibration, employs pure image-based registration, and does not utilize any vendor-specific hardware or software features In the open air, where there is no needle-tissue interaction, we systematically achieved an accuracy better than 1 mm in hitting targets at 5-8 cm from the fulcrum point In the phantom, the orientation accuracy was 0 6 degrees, and the distance between the needle tip, the target was 1 04 mm Experiments indicated that this robotic system is suitable for a variety of percutaneous clinical applications

}, keywords = {Biopsy, Computer-Assisted, Humans, Image Processing, Imaging, instrumentation, instrumentation/methods, Needle, Phantoms, Robotics, Surgery, Tomography, User-Computer Interface, X-Ray Computed}, doi = {10 1002/igs 10024}, url = {http://dx doi org/10 1002/igs 10024}, author = {Ken Masamune and Gabor Fichtinger and Alexandru Patriciu and Robert Susil and Russell H. Taylor and Louis Kavoussi and James Anderson and Ichiro Sakuma and Takeyoshi Dohi and Dan Stoianovici} }