@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 {Hefny2008, title = {Quantification of edematic effects in prostate brachytherapy interventions}, journal = {Medical image computing and computer-assisted intervention (MICCAI)}, volume = {11}, number = {Pt 2}, year = {2008}, pages = {493{\textendash}500}, publisher = {School of Computing, Queen{\textquoteright}s University, Kingston, Ontario, Canada}, abstract = {

We present a quantitative model to analyze the detrimental effects of for edema on the quality of prostate brachytherapy implants We account for both tissue expansion, implant migration by mapping intra-operative ultrasound, post-implant CT We pre-process the ultrasound with a phase congruency filter, and map it to the volume CT using a B-spline deformable mutual information similarity metric To test the method, we implanted a standard training phantom with 48 seeds, imaged the phantom with ultrasound, CT, registered the two for ground truth Edema was simulated by distorting the CT volume by known transformations The objective was to match the distorted implant to the intra-operative ultrasound Performance was measured relative to ground truth We successfully mapped 100\% of deformed seeds to ground truth under edematic expansion up to 40\% of volume growth Seed matching performance was 98\% with random seed migration of 3mm superimposed on 10\% edematic volume growth This method promises to be clinically applicable as the first quantitative analysis tool to measure edematic implant deformations occurring between the operating room, post-operative CT imaging

}, keywords = {adverse effects, adverse effects/instrumentation, Algorithms, Automated, Brachytherapy, complications/radiotherapy, Computer-Assisted, Edema, etiology/radiography, Humans, Male, methods, Pattern Recognition, Prostatic Diseases, Prostatic Neoplasms, Prosthesis Implantation, Radiographic Image Enhancement, Radiographic Image Interpretation, Reproducibility of Results, Sensitivity, Specificity, Tomography, Treatment Outcome, X-Ray Computed}, author = {Mohamed Hefny and Purang Abolmaesumi and Zahra Karim-Aghaloo and David Gobbi and Randy Ellis and Gabor Fichtinger} } @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 {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 {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} }