waashk/dblp huggingface dataset:
stabilization of image motion for robotic assisted beating heart surgery. the performance of robotic assisted minimally invasive beating heart surgery is a challenging task due to the rhythmic motion of the heart, which hampers delicate tasks such as small vessel anastomosis. in this paper, a virtual motion compensation scheme is proposed for stabilizing images from the surgical site. the method uses vision based 3d tracking to accurately infer cardiac surface deformation and augmented reality for rendering a motion stabilized view for improved surgical performance. the method forgoes the need of fiducial markers and can be integrated with the existing master-slave robotic consoles. the proposed technique is validated with both simulated surgical scenes with known ground truth and in vivo data acquired from a tecab procedure. the experimental results demonstrate the potential of the proposed technique in performing microscale tasks in a moving frame of reference with improved precision and repeatability.
automatic fetal measurements in ultrasound using constrained probabilistic boosting tree. automatic delineation and robust measurement of fetal anat-omical structures in 2d ultrasound images is a challenging task due to the complexity of the object appearance, noise, shadows, and quantity of information to be processed. previous solutions rely on explicit encoding of prior knowledge and formulate the problem as a perceptual grouping task solved through clustering or variational approaches. these methods are known to be limited by the validity of the underlying assumptions and cannot capture complex structure appearances. we propose a novel system for fast automatic obstetric measurements by directly exploiting a large database of expert annotated fetal anatomical structures in ultrasound images. our method learns to distinguish between the appearance of the object of interest and background by training a discriminative constrained probabilistic boosting tree classifier. this system is able to handle previously unsolved problems in this domain, such as the effective segmentation of fetal abdomens. we show results on fully automatic measurement of head circumference, biparietal diameter, abdominal circumference and femur length. unparalleled extensive experiments show that our system is, on average, close to the accuracy of experts in terms of segmentation and obstetric measurements. finally, this system runs under half second on a standard dual-core pc computer.
simultaneous segmentation, kinetic parameter estimation, and uncertainty visualization of dynamic pet images. we develop a segmentation technique for dynamic pet incorporating the physiological parameters for different regions via kinetic modeling. we demonstrate the usefulness of our technique on fifteen [11c] raclopride simulated pet images. we show qualitatively and quantitatively that the physiologically based algorithm outperforms two classical segmentation techniques. further, we derive a formula to compute and visualize the uncertainty encountered during the segmentation.
instrumentation for epidural anesthesia. a low-cost, sterilizable and unobtrusive instrumentation device was developed to quantify and study the loss-of-resistance technique in epidural anesthesia. in the porcine study, the rapid fall of the applied force, plunger displacement and fluid pressure, and the oral indication of the anesthesiologists were shown to be consistent with the loss-of-resistance. a model based on fluid leakage was developed to estimate the pressure from the force and displacement measurements, so that the pressure sensor could be omitted in human studies. in both human (in vivo) and porcine (in vitro) subjects, we observed that the ligamentum flavum is less amenable to saline injection than the interspinous ligament.
eye-gaze driven surgical workflow segmentation. in today's climate of clinical governance there is growing pressure on surgeons to demonstrate their competence, improve standards and reduce surgical errors. this paper presents a study on developing a novel eye-gaze driven technique for surgical assessment and workflow recovery. the proposed technique investigates the use of a parallel layer perceptor (plp) to automate the recognition of a key surgical step in a porcine laparoscopic cholecystectomy model. the classifier is eye-gaze contingent but combined with image based visual feature detection for improved system performance. experimental results show that by fusing image instrument likelihood measures, an overall classification accuracy of 75% is achieved.
quantifying heterogeneity in dynamic contrast-enhanced mri parameter maps. simple summary statistics of dynamic contrast-enhanced mri (dce-mri) parameter maps (e.g. the median) neglect the spatial arrangement of parameters, which appears to carry important diagnostic and prognostic information. this paper describes novel statistics that are sensitive to both parameter values and their spatial arrangement. binary objects are created from 3-d dce-mri parameter maps by "extruding" each voxel into a fourth dimension; the extrusion distance is proportional to the voxel's value. the following statistics are then computed on these 4-d binary objects: surface area, volume, surface area to volume ratio, and box counting (fractal) dimension. an experiment using 4 low and 5 high grade gliomas showed significant differences between the two grades for box counting dimension computed for extruded ve maps, surface area of extruded ktrans and ve maps and the volume of extruded ve maps (all p < 0.05). an experiment using 18 liver metastases imaged before and after treatment with a vascular endothelial growth factor (vegf) inhibitor showed significant differences for surface area to volume ratio computed for extruded ktrans and ve maps (p = 0.0013 and p = 0.045 respectively).
a novel 3d multi-scale lineness filter for vessel detection. the branching pattern and geometry of coronary microvessels are of high interest to understand and model the blood flow distribution and the processes of contrast invasion, ischemic changes and repair in the heart in detail. analysis is performed on high resolution, 3d volumes of the arterial microvasculature of entire goat hearts, which are acquired with an imaging cryomicrotome. multi-scale vessel detection is an important step required for a detailed quantitative analysis of the coronary microvasculature. based on visual inspection, the derived lineness filter shows promising results on real data and digital phantoms, on the way towards accurate computerized reconstructions of entire coronary trees. the novel lineness filter exploits the local first and second order multi-scale derivatives in order to give an intensity-independent response to line centers and to suppress unwanted responses to steep edges.
smt: split and merge tractography for dt-mri. diffusion tensor magnetic resonance imaging (dt-mri) based fiber tractography aims at reconstruction of the fiber network of brain. most commonly employed techniques for fiber tractography are based on the numerical integration of the principal diffusion directions. although these approaches generate intuitive and easy to interpret results, they are prone to cumulative errors and mostly discard the stochastic nature of dt-mri data. the proposed split & merge tractography (smt) technique aims at overcoming the drawbacks of fiber tractography by incorporating it with markov chain monte carlo techniques. smt is based on clustering diversely distributed short fiber tracts based on their inter-connectivity. smt also provides real-time interaction to adjust a user defined confidence level for clustering.
real-time spect and 2d ultrasound image registration. in this paper we present a technique for fully automatic, real-time 3d spect (single photon emitting computed tomography) and 2d ultrasound image registration. we use this technique in the context of kidney lesion diagnosis. our registration algorithm allows a physician to perform an ultrasound exam after a spect image has been acquired and see in real time the registration of both modalities. an automatic segmentation algorithm has been implemented in order to display in 3d the positions of the acquired us images with respect to the organs.
shape registration by simultaneously optimizing representation and transformation. this paper proposes a novel approach that achieves shape registration by optimizing shape representation and transformation simultaneously, which are modeled by a constrained gaussian mixture model (gmm) and a regularized thin plate spline respectively. the problem is formulated within a bayesian framework and solved by an expectation-maximum (em) algorithm. compared with the popular methods based on landmarks-sliding, its advantages include: (1) it can naturally deal with shapes of complex topologies and 3d dimension; (2) it is more robust against data noise; (3) the registration performance is better in terms of the generalization error of the resultant statistical shape model. these are demonstrated on both synthetic and biomedical shapes.
assessment of perceptual quality for gaze-contingent motion stabilization in robotic assisted minimally invasive surgery. with the increasing sophistication of surgical robots, the use of motion stabilisation for enhancing the performance of micro-surgical tasks is an actively pursued research topic. the use of mechanical stabilisation devices has certain advantages, in terms of both simplicity and consistency. the technique, however, can complicate the existing surgical workflow and interfere with an already crowded mis operated cavity. with the advent of reliable vision-based real-time and in situ in vivo techniques on 3d-deformation recovery, current effort is being directed towards the use of optical based techniques for achieving adaptive motion stabilisation. the purpose of this paper is to assess the effect of virtual stabilization on foveal/parafoveal vision during robotic assisted mis. detailed psychovisual experiments have been performed. results show that stabilisation of the whole visual field is not necessary and it is sufficient to perform accurate motion tracking and deformation compensation within a relatively small area that is directly under foveal vision. the results have also confirmed that under the current motion stabilisation regime, the deformation of the periphery does not affect the visual acuity and there is no indication of the deformation velocity of the periphery affecting foveal sensitivity. these findings are expected to have a direct implication on the future design of visual stabilisation methods for robotic assisted mis.
3-d analysis of cortical morphometry in differential diagnosis of parkinson's plus syndromes: mapping frontal lobe cortical atrophy in progressive supranuclear palsy patients. with the ability to study brain anatomy in vivo using magnetic resonance imaging, studies on regional brain atrophy suggest possible improvements for differential diagnosis of movement disorders with parkinsonian symptoms. in this study, we investigate effects of different parkinsonian syndromes on the cortical gray matter thickness and the geometric shape of the cerebral cortex. the study consists of a total of 24 patients with a diagnosis of probable progressive supranuclear palsy (psp), multiple systems atrophy (msa) or idiopathic parkinson's disease (ipd). we examine dense estimates of cortical gray matter thickness, sulcal depth, and measures of the curvature in a surface-based cortical morphometry analysis framework. group difference results indicate higher cortical atrophy rate in the frontal lobe in psp patients when compared to either msa or ipd. these findings are indicative of the potential use of routine mri and cortical morphometry in performing differential diagnosis in psp, msa and ipd.
longitudinal cortical registration for developing neonates. understanding the rapid evolution of cerebral cortical surfaces in developing neonates is essential in order to understand normal human brain development and to study anatomical abnormalities in preterm infants. several methods to model and align cortical surfaces for cross-sectional studies have been developed. however, the registration of cortical surfaces extracted from neonates across different gestational ages for longitudinal studies remains difficult because of significant cerebral growth. in this paper, we present an automatic cortex registration algorithm, based on surface relaxation followed by non-rigid surface registration. this technique aims to establish the longitudinal spatial correspondence of cerebral cortices for the developing brain in neonates. the algorithm has been tested on 5 neonates. each infant has been scanned at three different time points. quantitative results are obtained by propagating sulci across multiple gestational ages and computing the overlap ratios with manually established ground-truth.
rotational roadmapping: a new image-based navigation technique for the interventional room. for decades, conventional 2d-roadmaping has been the method of choice for image-based guidewire navigation during endovascular procedures. only recently have 3d-roadmapping techniques become available that are based on the acquisition and reconstruction of a 3d image of the vascular tree. in this paper, we present a new image-based navigation technique called roro (rotational roadmapping) that eliminates the guess-work inherent to the conventional 2d method, but does not require a 3d image. our preliminary clinical results show that there are situations in which roro is preferred over the existing two methods, thus demonstrating potential for filling a clinical niche and complementing the spectrum of available navigation tools.
error analysis of calibration materials on dual-energy mammography. dual-energy mammography can suppress the contrast between adipose and glandular tissues and improve the detectability of microcalcifications (mcs). in clinical dual-energy mammography, imaging object is human breast, while in calibration measurements, only phantoms of breast-tissue-equivalent material can be used. the composition and density differences between calibration materials and human breast bring the differences of linear attenuation coefficient which lead to the calculation errors in dual-energy imaging. in this paper, the magnitude of mc thickness error from calibration materials has been analyzed using a first-order propagation of error analysis. this analysis shows that the thickness error from calibration materials ranges from dozens to thousands of microns which can not be ignored when carrying out dual-energy calculations. the evaluation of several popular phantoms shows that it is of great importance to adopt the phantom materials approaching human breast most.
is a single energy functional sufficient? adaptive energy functionals and automatic initialization. energy functional minimization is an increasingly popular technique for image segmentation. however, it is far too commonly applied with hand-tuned parameters and initializations that have only been validated for a few images. fixing these parameters over a set of images assumes the same parameters are ideal for each image. we highlight the effects of varying the parameters and initialization on segmentation accuracy and propose a framework for attaining improved results using image adaptive parameters and initializations. we provide an analytical definition of optimal weights for functional terms through an examination of segmentation in the context of image manifolds, where nearby images on the manifold require similar parameters and similar initializations. our results validate that fixed parameters are insufficient in addressing the variability in real clinical data, that similar images require similar parameters, and demonstrate how these parameters correlate with the image manifold. we present significantly improved segmentations for synthetic images and a set of 470 clinical examples.
quantifying calcification in the lumbar aorta on x-ray images. in this paper we propose to use inpainting to estimate the severity of atherosclerotic plaques from x-ray projections. inpainting allows to "remove" the plaque and estimate what the background image for an uncalcified aorta would have looked like. a measure of plaque severity can then be derived by subtracting the inpainting from the original image. in contrast to the current standard of categorical calcification scoring from x-rays, our method estimates both the size and the density of calcified areas and provides a continuous severity score, thus allowing for measurement of more subtle differences. we discuss a class of smooth inpainting methods, compare their ability to reconstruct the original images, and compare the inpainting based calcification score to the conventional categorical score in a longitudinal study on 49 patients addressing correlations of the calcification scores with hypertension, a known cardiovascular risk factor.
functional near infrared spectroscopy in novice and expert surgeons - a manifold embedding approach. monitoring expertise development in surgery is likely to benefit from evaluations of cortical brain function. brain behaviour is dynamic and nonlinear. the aim of this paper is to evaluate the application of a nonlinear dimensionality reduction technique to enhance visualisation of multidimensional functional near infrared spectroscopy (fnirs) data. manifold embedding is applied to prefrontal haemodynamic signals obtained during a surgical knot tying task from a group of 62 healthy subjects with varying surgical expertise. the proposed method makes no assumption about the functionality of the data set and is shown to be capable of recovering the intrinsic low dimensional structure of in vivo brain data. after manifold embedding, earth mover's distance (emd) is used to quantify different patterns of cortical behaviour associated with surgical expertise and analyse the degree of inter-hemispheric channel pair symmetry.
a probabilistic model for haustral curvatures with applications to colon cad. among the many features used for classification in computer-aided detection (cad) systems targeting colonic polyps, those based on differences between the shapes of polyps and folds are most common. we introduce here an explicit parametric model for the haustra or colon wall. the proposed model captures the overall shape of the haustra and we use it to derive the probability distribution of features relevant to polyp detection. the usefulness of the model is demonstrated through its application to a colon cad algorithm.
predictive k-plsr myocardial contractility modeling with phase contrast mr velocity mapping. with the increasing versatility of cmr, further understanding of intrinsic contractility of the myocardium can be achieved by performing subject-specific modeling by integrating structural and functional information available. the recent introduction of the virtual tagging framework allows for visualization of the localized deformation of the myocardium based on phase contrast myocardial velocity mapping. the purpose of this study is to examine the use of a non-linear, kernel-partial least squares regression (k-plsr) predictive motion modeling scheme for the virtual tagging framework. the method allows for the derivation of a compact non-linear deformation model such that the entire deformation field can be predicted by a limited number of control points. when applied to virtual tagging, the technique can be used to predictively guide the mesh refinement based on the motion of the coarse grid, thus greatly reducing the search space and increasing the convergence speed of the algorithm. the effectiveness and numerical accuracy of the proposed technique are assessed with both numerically simulated data sets and in vivo phase contrast cmr velocity mapping from a group of 7 subjects. the technique presented has a distinct advantage over the conventional mesh refinement scheme and brings cmr myocardial contractility analysis closer to routine clinical practice.
on fiducial target registration error in the presence of anisotropic noise. we study the effect of anisotropic noise on target registration error (tre) by using a tracked and calibrated stylus tip as the fiducial registration application. we present a simple, efficient unscented kalman filter algorithm that is suitable for fiducial registration even with a small number of fiducials. we also derive an equation that predicts tre under anisotropic noise. the predicted tre values are shown to closely match the simulated tre values achieved using our ukf-based algorithm.
a probabilistic framework for tracking deformable soft tissue in minimally invasive surgery. the use of vision based algorithms in minimally invasive surgery has attracted significant attention in recent years due to its potential in providing in situ 3d tissue deformation recovery for intra-operative surgical guidance and robotic navigation. thus far, a large number of feature descriptors have been proposed in computer vision but direct application of these techniques to minimally invasive surgery has shown significant problems due to free-form tissue deformation and varying visual appearances of surgical scenes. this paper evaluates the current state-of-the-art feature descriptors in computer vision and outlines their respective performance issues when used for deformation tracking. a novel probabilistic framework for selecting the most discriminative descriptors is presented and a bayesian fusion method is used to boost the accuracy and temporal persistency of soft-tissue deformation tracking. the performance of the proposed method is evaluated with both simulated data with known ground truth, as well as in vivo video sequences recorded from robotic assisted mis procedures.
unbiased white matter atlas construction using diffusion tensor images. this paper describes an algorithm for unbiased construction of white matter (wm) atlases using full information available to diffusion tensor (dt) images. the key component of the proposed algorithm is a novel dt image registration method that leverages metrics comparing tensors as a whole and optimizes tensor orientation explicitly. the problem of unbiased atlas construction is formulated using the approach proposed by joshi et al., i.e., the unbiased wm atlas is determined by finding the mappings that best match the atlas to the images in the population and have the least amount of deformation. we show how the proposed registration algorithm can be adapted to approximately find the optimal atlas. the utility of the proposed approach is demonstrated by constructing a wm atlas of 13 subjects. the presented dt registration method is also compared to the approach of matching dt images by aligning their fractional anisotropy images using large-deformation image registration methods. our results suggest that using full tensor information can better align the orientations of wm fiber bundles.
a multiphysics simulation of a healthy and a diseased abdominal aorta. abdominal aortic aneurysm is a potentially life-threatening disease if not treated adequately. its pathogenesis is complex and multifactorial and is still not fully understood. many biochemical and biomechanical mechanisms have been identified as playing a role in the formation of aneurysms but it is as yet unclear what triggers the process. we investigated the role of the relevant biomechanical factors, in particular the wall shear stress and the intramural wall stress by simulating fluid structure interaction between the blood flow and the deforming arterial wall in a healthy abdominal aortic bifurcation, the preferred location of the disease. we then extended this study by introducing a hypothetical weakening of the aortic wall. intramural wall stress was considerably higher and wall shear stress considerably lower in this configuration, supporting the hypothesis that biomechanical aneurysmal growth factors are self-sustaining.