waashk/dblp huggingface dataset:
construction of a statistical surgical plan atlas for automated 3d planning of femoral component in total hip arthroplasty. the problem of automating preoperative planning of the femoral component (stem) for total hip arthroplasty (tha) is addressed. in our previous method, time-consuming trial-and-error processes were involved in parameter tuning of the objective function. this problem prevents application in different stem systems. to overcome this problem, a statistical surgical plan atlas (sspa) is constructed from training datasets of stem planning. the sspa represents the average and variance of the distance distribution on the stem surface to the femoral canal surface. that is, it encodes the distribution of the degree of contact preferred by the surgeon. automated planning is performed by minimizing the squared difference between distributions of the sspa and planning solution. the proposed method involves no parameter tuning to define the objective function that evaluates differences from the planning the surgeon prefers. experimental evaluations showed that the proposed method renders parameter tuning unnecessary while it still provides comparable accuracy to the previous method.
physically-based validation of deformable medical image registration. we propose a new approach for validating deformable image registration algorithms. since difference images do not necessarily reflect the 3d correspondence of organs, we propose to use the deformation fields generated in our fem-based simulations to assess the displacement resulted from other registration methods. unlike traditional fem-based registration methods, the boundary condition for the target organ is not given explicitly. instead it is driven by inter-organ contact forces generated by boundary conditions on surrounding organs to reduce the uncertainty induced by geometry-based surface matching. to validate our system, real ct images of the male pelvis are analyzed, and the prostate can be reasonably registered without matching its surface to the image. several registration methods are then evaluated using our system.
harmonic surface mapping with laplace-beltrami eigenmaps. in this paper we propose a novel approach for the mapping of 3d surfaces. with the reeb graph of laplace-beltrami eigenmaps, our method automatically detects stable landmark features intrinsic to the surface geometry and use them as boundary conditions to compute harmonic maps to the unit sphere. the resulting maps are diffeomorphic, robust to natural pose variations, and establish correspondences for geometric features shared across population. in the experiments, we demonstrate our method on three subcortical structures: the hippocampus, putamen, and caudate nucleus. a group study is also performed to generate a statistically significant map of local volume losses in the hippocampus of patients with secondary progressive multiple sclerosis.
effective incorporation of spatial information in a mutual information based 3d-2d registration of a ct volume to x-ray images. this paper addresses the problem of estimating the 3d rigid pose of a ct volume of an object from its 2d x-ray projections. we use maximization of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. however, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. in this paper, instead of directly maximizing mutual information, we propose to use a variational approximation derived from the kullback-leibler bound. spatial information is then incorporated into this variational approximation using a markov random field model. the newly derived similarity measure has a least-squares form and can be effectively minimized by a multi-resolution levenberg-marquardt optimizer. experimental results are presented on x-ray and ct datasets of a plastic phantom and a cadaveric spine segment.
reducing motion artifacts in 3-d breast ultrasound using non-linear registration. automated full-field 3-d breast ultrasound (3dbus) has a high potential as a reproducible method for screening and intervention. consecutive linear transducer scans yield a consistent breast ultrasound volume, yet individual slices are prone to tissue deformation and motion. to compensate resulting image distortions, we propose an efficient non-rigid registration method applied sequentially to pairs of 3dbus volume slices, optionally either on-line or in post-processing. a quantitative evaluation of the method on synthetic deformations shows subvoxel registration accuracy. first application to clinical breast us images and preliminary results confirmed effectiveness and accuracy of the method.
the zernike expansion - an example of a merit function for 2d/3d registration based on orthogonal functions. current merit functions for 2d/3d registration usually rely on comparing pixels or small regions of images using some sort of statistical measure. problems connected to this paradigm the sometimes problematic behaviour of the method if noise or artefacts (for instance a guide wire) are present on the projective image. we present a merit function for 2d/3d registration which utilizes the decomposition of the x-ray and the drr under comparison into orthogonal zernike moments; the quality of the match is assessed by an iterative comparison of expansion coefficients. results in a imaging study on a physical phantom show that --- compared to standard cross-correlation --- the zernike moment based merit function shows better robustness if histogram content in images under comparison is different, and that time expenses are comparable if the merit function is constructed out of a few significant moments only.
quantification of edematic effects in prostate brachytherapy interventions. we present a quantitative model to analyze the detrimental effects of edema on the quality of prostate brachytherapy implants. we account for both tissue expansion and implant migration by mapping intra-operative ultrasound and 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 and ct and 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 and post-operative ct imaging.
probabilistic anatomo-functional parcellation of the cortex: how many regions?. understanding brain structure and function entails the inclusion of anatomical and functional information in a common space, in order to study how these different informations relate to each other in a population of subjects. in this paper, we revisit the parcellation model and explicitly combine anatomical features, i.e. a segmentation of the cortex into gyri, with a functional information under the form of several cortical maps, which are used to further subdivide the gyri into functionally consistent regions. a probabilistic model is introduced, and the parcellation model is estimated using a variational bayes approach. the number of regions in the model is validated based on cross-validation. it is found that about 250 patches of cortex can be delineated both in the left and right hemisphere based on this procedure.
visualization tools for high angular resolution diffusion imaging. there is a major effort in medical imaging to develop algorithms to extract information from dti and hardi, which provide detailed information on brain integrity and connectivity. as the images have recently advanced to provide extraordinarily high angular resolution and spatial detail, including an entire manifold of information at each point in the 3d images, there has been no readily available means to view the results. this impedes developments in hardi research, which need some method to check the plausibility and validity of image processing operations on hardi data or to appreciate data features or invariants that might serve as a basis for new directions in image segmentation, registration, and statistics. we present a set of tools to provide interactive display of hardi data, including both a local rendering application and an off-screen renderer that works with a web-based viewer. visualizations are presented after registration and averaging of hardi data from 90 human subjects, revealing important details for which there would be no direct way to appreciate using conventional display of scalar images.
dynamic view expansion for enhanced navigation in natural orifice transluminal endoscopic surgery. natural orifice transluminal endoscopic surgery (notes) is an emerging surgical technique with increasing global interest. it has recently transcended the boundaries of clinical experiments towards initial clinical evaluation. although profound benefits to the patient have been demonstrated, notes requires highly skilled endoscopists for it to be performed safely and successfully. this predominantly reflects the skill required to navigate a flexible endoscope through a spatially complex environment. this paper presents a method to extend the visual field of the surgeon without compromising on the safety of the patient. the proposed dynamic view expansion uses a novel parallax correction scheme to provide enhanced visual cues that aid the navigation and orientation during notes surgery in periphery, while leaving the focal view undisturbed. the method was validated using a natural orifice simulated surgical environment and demonstrated on in vivo porcine data.
fast virtual stenting with deformable meshes: application to intracranial aneurysms. intracranial stents are medical devices that are becoming increasingly popular in the treatment of intracranial aneurysms. a methodology that predicts the released stent configuration prior to intervention has the potential to support the physician in the selection of the optimal approach for a specific patient. this paper proposes a fast virtual stenting technique based on constrained simplex deformable models that is able to virtually release stents in arbitrarily shaped vessel and aneurysm models. the technique effectively embeds the geometrical properties of the stent (cell design, strut size and shape and angles between struts) and achieves favorable execution times of the order of one minute.
software strategy for robotic transperineal prostate therapy in closed-bore mri. a software strategy to provide intuitive navigation for mri-guided robotic transperineal prostate therapy is presented. in the system, the robot control unit, the mri scanner, and open-source navigation software are connected to one another via ethernet to exchange commands, coordinates, and images. six states of the system called "workphases" are defined based on the clinical scenario to synchronize behaviors of all components. the wizard-style user interface allows easy following of the clinical workflow. on top of this framework, the software provides features for intuitive needle guidance: interactive target planning; 3d image visualization with current needle position; treatment monitoring through real-time mri. these features are supported by calibration of robot and image coordinates by the fiducial-based registration. the performance test shows that the registration error of the system was 2.6 mm in the prostate area, and it displayed real-time 2d image 1.7 s after the completion of image acquisition.
passive ventricular mechanics modelling using mri of structure and function. patients suffering from dilated cardiomyopathy or myocardial infarction can develop left ventricular (lv) diastolic impairment. the lv remodels its structure and function to adapt to pathophysiological changes in geometry and loading conditions and this remodeling process can alter the passive ventricular mechanics. in order to better understand passive ventricular mechanics, a lv finite element model was developed to incorporate physiological and mechanical information derived fromin vivo magnetic resonance imaging (mri) tissue tagging, in vivo lv cavity pressure recording and ex vivo diffusion tensor mri (dtmri) of a canine heart. mri tissue tagging enables quantitative evaluation of cardiac mechanical function with high spatial and temporal resolution, whilst the direction of maximum water diffusion (the primary eigenvector) in each voxel of a dtmri directly correlates with the myocardial fibre orientation. this model was customized to the geometry of the canine lv during diastasis by fitting the segmented epicardial and endocardial surface data from tagged mri using nonlinear finite element fitting techniques. myofibre orientations, extracted from dtmri of the same heart, were incorporated into this geometric model using a free form deformation methodology. pressure recordings, temporally synchronized to the tissue tagging mri data, were used to simulate the lv deformation during diastole. simulation of the diastolic lv mechanics allowed us to estimate the stiffness of the passive lv myocardium based on kinematic data obtained from tagged mri. this integrated physiological model will allow more insight into the regional passive diastolic mechanics of the lv on an individualized basis, thereby improving our understanding of the underlying structural basis of mechanical dysfunction in pathological conditions.
an incremental method for registering electroanatomic mapping data to surface mesh models of the left atrium. we present a method for registering position and orientation data collected from an electroanatomic mapping system (ems) to a surface mesh based on segmented computed tomography (ct) or magnetic resonance (mr) images of the left atrium. our algorithm is based on the unscented particle filter (upf) for stochastic state estimation. using an intracardiac echo (ice) ultrasound catheter with mounted mapping sensor, we acquire ultrasound images of the atrium from multiple configurations and iteratively determine the catheter's pose with respect to anatomy. after considering less than a minute's worth of ice data, the algorithm converges to an accurate pose estimate which, in turn, yields the registration parameters transforming ems coordinates to mesh coordinates. the iterative framework of the upf allows us to be robust to unmodeled ems noise and drift, problems which complicate traditional registration methods assuming regularity in image data structure.
gpu accelerated non-rigid registration for the evaluation of cardiac function. we present a method for the fast and efficient tracking of motion in cardiac magnetic resonance (cmr) cines. a gpu accelerated levenberg-marquardt non-linear least squares optimization procedure for finite element non-rigid registration was implemented on an nvidia graphics card using the opengl environment. points were tracked from frame to frame using forward and backward incremental registration. the inner (endocardial) and outer (epicardial) boarders of the heart were tracked in six short axis cines with ~25 frames through the cardiac cycle in 36 patients with vascular disease. contours placed by two independent expert observers using a semi-automatic ventricular analysis program (cim version 4.6) were used as the gold standard. the method took 0.5 seconds per frame, and the maximum hausdorff errors were less than 2 mm on average which was of the same order as the expert inter-observer error. in conclusion, gpu accelerated levenberg-marquardt non-linear optimization enables fast and accurate tracking of cardiac motion in cmr images.
the effect of automated marker detection on in vivo volumetric stent reconstruction. new drug eluting stents are less radiopaque than bare metal stents and therefore difficult to see with conventional x-ray coronary angiography. 2d stentboost and intravascular ultrasound (ivus) are routinely used to evaluate stent deployment and vessel apposition during a percutaneous coronary intervention. ivus images give cross-sectional information about the stent lumen and surrounding tissue. 2d stentboost is a boosted angiogram sequence and visualizes the geometry of the deployed stent from a fixed viewing direction. three-dimensional motion compensated volumetric stent reconstruction has been developed to give insight into the 3d geometry of the stent. markers on the balloon wire are used to motion compensate cardiac rotational angiography acquisitions. in this paper we present the effect of automated marker detection on in vivo volumetric cardiac stent reconstructions. automated or semi-automated marker detection reduces user interaction, potentially reduces total processing time, and increases detection results which leads to higher quality of stent reconstructions.
models of normal variation and local contrasts in hippocampal anatomy. we develop a model of continuous spherical shapes and use it to analyze the anatomy of the hippocampus. to account for the geometry of bends and folds, the model relies on a geodesic metric that is sensitive to first-order deformations. we construct an atlas of the hippocampus as a mean shape and develop statistical models to characterize quantitative and qualitative normal shape variation. we also develop a localization tool to identify local contrasts in the anatomy of different populations. the tool is applied to the detection, characterization and visualization of anatomical differences such as local enlargement and gains in volume on the right hippocampus of blind subjects.
a robot assisted hip fracture reduction with a navigation system. a fracture reduction robot is described as assisting in safe and precise fracture reduction. the robot is connected with pins that are inserted into the patient's bone fragments, together with a customized jig. the robot has six degrees of freedom with high precision, so that precise fracture reduction can be conducted. the failsafe unit of the fracture reduction robot can mitigate excessive reduction force that may cause complications such as avascular necrosis. we have integrated the fracture reduction robot with a navigation system that tracks the relative position of the bone fragments and generates the reduction path. the integrated system is evaluated with the simulated fracture reduction of a hip fracture model (n=8). three-dimensional parameters related to the mechanical axis-the proximal femur angle, the distal femur angle, and the length of the mechanical axis-were evaluated by comparing the normal values with those after reduction; these average differences are 1.76°, 0.28° and 0.76mm, respectively. the automated fracture reduction feature makes it possible for medical staff to work at a distance from radiation sources; for patients, the integrated fracture reduction system has the potential to reduce fractures with high precision.
mri compatibility of robot actuation techniques - a comparative study. this paper reports an experimental evaluation of the following three different mri-compatible actuators: a shinsei ultrasonic motor, a nanomotion ultrasonic motor and a pneumatic cylinder actuator. we report the results of a study comparing the effect of these actuators on the signal to noise ratio (snr) of mri images under a variety of experimental conditions. evaluation was performed with the controller inside and outside the scanner room and with both 1.5t and 3t mri scanners. pneumatic cylinders function with no loss of snr with controller both inside and outside of the scanner room. the nanomotion motor performs with moderate loss of snr when moving during imaging. the shinsei is unsuitable for motion during imaging. all may be used when motion is appropriately interleaved with imaging cycles.
gaze-contingent 3d control for focused energy ablation in robotic assisted surgery. the use of focused energy delivery in robotic assisted surgery for atrial fibrillation requires accurate prescription of ablation paths. in this paper, an original framework based on fusing human and machine vision for providing gaze-contigent control in robotic assisted surgery is provided. with the proposed method, binocular eye tracking is used to estimate the 3d fixations of the surgeon, which are further refined by considering the camera geometry and the consistency of image features at reprojected fixations. nonparametric clustering is then used to optimize the point distribution to provide an accurate ablation path. for experimental validation, a study where eight subjects prescribe an ablation path on the right atrium of the heart using only their gaze control is presented. the accuracy of the proposed method is validated using a phantom heart model with known 3d ground truth.
sparse approximation of currents for statistics on curves and surfaces. computing, processing, visualizing statistics on shapes like curves or surfaces is a real challenge with many applications ranging from medical image analysis to computational geometry. modelling such geometrical primitives with currents avoids feature-based approach as well as point-correspondence method. this framework has been proved to be powerful to register brain surfaces or to measure geometrical invariants. however, if the state-of-the-art methods perform efficiently pairwise registrations, new numerical schemes are required to process groupwise statistics due to an increasing complexity when the size of the database is growing. statistics such as mean and principal modes of a set of shapes often have a heavy and highly redundant representation. we propose therefore to find an adapted basis on which mean and principal modes have a sparse decomposition. besides the computational improvement, this sparse representation offers a way to visualize and interpret statistics on currents. experiments show the relevance of the approach on 34 sets of 70 sulcal lines and on 50 sets of 10 meshes of deep brain structures.
physical-space refraction-corrected transmission ultrasound computed tomography made computationally practical. transmission ultrasound computed tomography (ct) is strongly affected by the acoustic refraction properties of the imaged tissue, and proper modeling and correction of these effects is crucial to achieving high-quality image reconstructions. a method that can account for these refractive effects solves the governing eikonal equation within an iterative reconstruction framework, using a wave-front tracking approach. excellent results can be obtained, but at considerable computational expense. here, we report on the acceleration of three eikonal solvers (fast marching method (fmm), fast sweeping method (fsm), fast iterative method (fim)) on three computational platforms (commodity graphics hardware (gpus), multi-core and cluster cpus), within this refractive transmission ultrasound ct framework. our efforts provide insight into the capabilities of the various architectures for acoustic wave-front tracking, and they also yield a framework that meets the interactive demands of clinical practice, without a loss in reconstruction quality.