@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 {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} }