@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} } @article {Metaxas2008a, title = {Medical image computing and computer-assisted intervention{\textendash}Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2008 Preface}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {11}, number = {Pt 1}, year = {2008}, pages = {V{\textendash}VII}, publisher = {Rutgers University, Division of Computer, Information Sciences, Piscataway, NJ 08854-8019, USA}, keywords = {Algorithms, Computer-Assisted, Image Enhancement, Image Interpretation, Interventional, methods, Radiography, Surgery, trends}, author = {Dimitris Metaxas and Leon Axel and Gabor Fichtinger and Gabor Szekely} } @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 {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 {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 {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 {Boctor2005, title = {Real-time quality control of tracked ultrasound}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {8}, number = {Pt 1}, year = {2005}, pages = {621{\textendash}630}, abstract = {

The overwhelming majority of intra-operative hazard situations in tracked ultrasound (US) systems are attributed to failure of registration between tracking, imaging coordinate frames We introduce a novel methodology for eal-time in-vivo quality control of tracked US systems, in order to capture registration failures during the clinical procedure In effect, we dynamically recalibrate the tracked US system for rotation, scale factor, and in-plane position offset up to a scale factor We detect any unexpected change in these parameters through capturing discrepancies in the resulting calibration matrix, thereby assuring quality (accuracy, consistency) of the tracked system No phantom is used for the recalibration We perform the task of quality control in the background, transparently to the clinical user while the subject is being scanned We present the concept, mathematical formulation, and experimental evaluation in-vitro This new method can play an important role in guaranteeing accurate, consistent, and reliable performance of tracked ultrasound

}, keywords = {Algorithms, Computer Systems, Computer-Assisted, Health Care, Humans, Image Enhancement, Image Interpretation, Interventional, methods, Quality Assurance, Quality Control, Reproducibility of Results, Sensitivity, Specificity, Surgery, Ultrasonography, User-Computer Interface}, author = {Emad Boctor and Iulian Iordachita and Gabor Fichtinger and Gregory D. Hager} } @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} }