Showing papers by "David H. Laidlaw published in 2006"

An Introduction to Visualization of Diffusion Tensor Imaging and Its Applications

Abstract: Water diffusion is anisotropic in organized tissues such as white matter and muscle Diffusion tensor imaging (DTI), a non-invasive MR technique, measures water self-diffusion rates and thus gives an indication of the underlying tissue microstructure The diffusion rate is often expressed by a second-order tensor Insightful DTI visualization is challenging because of the multivariate nature and the complex spatial relationships in a diffusion tensor field This chapter surveys the different visualization techniques that have been developed for DTI and compares their main characteristics and drawbacks We also discuss some of the many biomedical applications in which DTI helps extend our understanding or improve clinical procedures We conclude with an overview of open problems and research directions

CAVE and fishtank virtual-reality displays: a qualitative and quantitative comparison

Abstract: We present the results from a qualitative and quantitative user study comparing fishtank virtual-reality (VR) and CAVE displays. The results of the qualitative study show that users preferred the fishtank VR display to the CAVE system for our scientific visualization application because of perceived higher resolution, brightness and crispness of imagery, and comfort of use. The results of the quantitative study show that users performed an abstract visual search task significantly more quickly and more accurately on the fishtank VR display system than in the CAVE. The same study also showed that visual context had no significant effect on task performance for either of the platforms. We suggest that fishtank VR displays are more effective than CAVEs for applications in which the task occurs outside the user's reference frame, the user views and manipulates the virtual world from the outside in, and the size of the virtual object that the user interacts with is smaller than the user's body and fits into the fishtank VR display. The results of both studies support this proposition

Super-resolution registration using tissue-classified distance fields

Abstract: We present a method for registering the position and orientation of bones across multiple computed-tomography (CT) volumes of the same subject. The method is subvoxel accurate, can operate on multiple bones within a set of volumes, and registers bones that have features commensurate in size to the voxel dimension. First, a geometric object model is extracted from a reference volume image. We use then unsupervised tissue classification to generate from each volume to be registered a super-resolution distance field-a scalar field that specifies, at each point, the signed distance from the point to a material boundary. The distance fields and the geometric bone model are finally used to register an object through the sequence of CT images. In the case of multiobject structures, we infer a motion-directed hierarchy from the distance-field information that allows us to register objects that are not within each other's capture region. We describe a validation framework and evaluate the new technique in contrast with grey-value registration. Results on human wrist data show average accuracy improvements of 74% over grey-value registration. The method is of interest to any intrasubject, same-modality registration applications where subvoxel accuracy is desired.

Simulation and visualization of topological defects in nematic liquid crystals

Abstract: We present a method of visualizing topological defects arising in numerical simulations of liquid crystals. The method is based on scientific visualization techniques developed to visualize second-rank tensor fields, yielding information not only on the local structure of the field but also on the continuity of these structures. We show how these techniques can be used to first locate topological defects in fluid simulations of nematic liquid crystals where the locations are not known a priori and then study the properties of these defects including the core structure. We apply these techniques to simulation data obtained by previous authors who studied a rapid quench and subsequent equilibration of a Gay-Berne nematic. The quench produces a large number of disclination loops which we locate and track with the visualization methods. We show that the cores of the disclination lines have a biaxial region and the loops themselves are of a hybrid wedge-twist variety.

A Kinematics-Based Method For Generating Cartilage Maps and Deformations in the Multi-Articulating Wrist Joint From CT Images

Abstract: We present a non-invasive method for estimating individual-specific cartilage maps directly from in vivo kine- matic data and computed tomography (CT) volume images, and a novel algorithm for computing cartilage surface deforma- tions. Our proposed cartilage model, a meshless incompressible height-field captures the physical properties important for estimating the shape, contact area, and deformation magnitude of cartilage at each articulation. This cartilage model can serve as an effective building block for a future forward-dynamic predictive model of the human wrist. I. INTRODUCTION The carpal cartilages in the wrist are among the least documented soft-tissue structures in human anatomy, impact- ing negatively our understanding of the many degenerative and repetitive-strain diseases afflicting this versatile joint. The reasons lie in the very versatile nature of the wrist articulation: its complexity and compactness (eight kidney- bean-sized bones) means cartilage is thinner than in other joints. Carpal cartilage is thus hard to image in vivo, although that is where its functional role in wrist kinematics would be most naturally investigated. In turn, examination in vitro requires invasive disruption of the articulation and thus results in artificially-imposed kinematics. We introduce a non-invasive, individual-specific carpal cartilage modeling approach that allows for the in vivo exploration of cartilage functional role. We present a method for estimating individual-specific cartilage maps (location and thickness) directly from in vivo kinematic data and computed tomography (CT) volume images, and a novel algorithm for computing cartilage surface deformations. Our proposed cartilage model, a meshless incompressible height- field captures the physical properties important for estimating the shape, contact area, and deformation magnitude of car- tilage at each articulation. The model is more complex and potentially more realistic than other current in vivo carpal cartilage models (1), while being faster to calculate than finite element approaches (2). Thus our model can serve as an effective building block for a future forward-dynamic predictive model of the human wrist.

Identification of fibers at risk for degeneration by diffusion tractography in patients at high risk for MS after a clinically isolated syndrome.

Abstract: Purpose Focal inflammatory/demyelinating lesions are thought to be the source of Wallerian degeneration or other injury to local, transiting fiber tracts in the brain or spinal cord in multiple sclerosis (MS). A methodology is established to isolate connections between focal demyelinating lesions and intersecting fibers to permit explicit analyses of the pathology of secondary fiber injury distant from the focal lesion. Materials and Methods A strategy is described and feasibility demonstrated in three patients with a clinically isolated syndrome and positive MRI (at high risk for MS). The strategy utilizes streamtube diffusion tractography to identify neuronal fibers that intersect a focal lesion and pass through a region of interest, in this case the corpus callosum, where distal (to focal lesion) interrogation can be accomplished. Results A sizeable fraction of the normal appearing white matter (NAWM) in the early stages of disease can be defined in the corpus callosum, which is distinctive in that this tissue connects to distant demyelinating lesions. Conclusion The new class of tissue called fibers-at-risk for degeneration (FAR) can be identified and interrogated by a variety of quantitative MRI methodologies to better understand neuronal degeneration in MS. J. Magn. Reson. Imaging 2006. Published 2006 Wiley-Liss, Inc.

Subjective Quantification of Perceptual Interactions among some 2D Scientific Visualization Methods

Abstract: We present an evaluation of a parameterized set of 2D icon-based visualization methods where we quantified how perceptual interactions among visual elements affect effective data exploration. During the experiment, subjects quantified three different design factors for each method: the spatial resolution it could represent, the number of data values it could display at each point, and the degree to which it is visually linear. The class of visualization methods includes Poisson-disk distributed icons where icon size, icon spacing, and icon brightness can be set to a constant or coupled to data values from a 2D scalar field. By only coupling one of those visual components to data, we measured filtering interference for all three design factors. Filtering interference characterizes how different levels of the constant visual elements affect the evaluation of the data-coupled element. Our novel experimental methodology allowed us to generalize this perceptual information, gathered using ad-hoc artificial datasets, onto quantitative rules for visualizing real scientific datasets. This work also provides a framework for evaluating visualizations of multi-valued data that incorporate additional visual cues, such as icon orientation or color

Techniques for the Visualization of Topological Defect Behavior in Nematic Liquid Crystals

Abstract: We present visualization tools for analyzing molecular simulations of liquid crystal (LC) behavior. The simulation data consists of terabytes of data describing the position and orientation of every molecule in the simulated system over time. Condensed matter physicists study the evolution of topological defects in these data, and our visualization tools focus on that goal. We first convert the discrete simulation data to a sampled version of a continuous second-order tensor field and then use combinations of visualization methods to simultaneously display combinations of contractions of the tensor data, providing an interactive environment for exploring these complicated data. The system, built using AVS, employs colored cutting planes, colored isosurfaces, and colored integral curves to display fields of tensor contractions including Westin's scalar cl, cp , and cs metrics and the principal eigenvector. Our approach has been in active use in the physics lab for over a year. It correctly displays structures already known; it displays the data in a spatially and temporally smoother way than earlier approaches, avoiding confusing grid effects and facilitating the study of multiple time steps; it extends the use of tools developed for visualizing diffusion tensor data, re-interpreting them in the context of molecular simulations; and it has answered long-standing questions regarding the orientation of molecules around defects and the conformational changes of the defects

Blood flow at arterial branches: complexities to resolve for the angioplasty suite

Abstract: This paper presents a case of interdisciplinary collaboration in building and using a set of tools to compute the flows in a branched artery, to compare them with prior physical flow visualization, and to interpret them with further users in mind. The geometry was taken for a typical epicardial coronary artery with a side branch. The incompressible Navier-Stokes equations were solved with the hybrid spectral/hp element solver Nektar. Some simulations were visualized in the CAVE, an immersive 3D stereo display environment, and selected features are described and interpreted.

Connectivity-Aware Sectional Visualization of 3D DTI Volumes using Perceptual Flat-Torus Coloring and Edge Rendering

Abstract: We present two new methods for visualizing cross-sections of 3D diffusion tensor magnetic resonance imaging (DTI) volumes. For each of the methods we show examples of visualizations of the corpus callosum in the midsagittal plane of several normal volunteers. In both methods, we start from points sampled on a regular grid on the cross-section and, from each point, generate integral curves in both directions following the principal eigenvector of the underlying diffusion tensor field. We compute an anatomically motivated pairwise distance measure between each pair of integral curves and assemble the measures to create a distance matrix. We next find a set of points in a plane that best preserves the calculated distances that are small—each point in this plane represents one of the original integral curves. Our first visualization method wraps this planar representation onto a flat-torus and then projects that torus into a visible portion of a perceptually uniform color space (L*a*b*). The colors for the paths are used to color the corresponding grid points on the original cross-section. The resulting image shows larger changes in color where neighboring integral curves differ more. Our second visualization method lays out the grid points on the cross section and connects the neighboring points with edges that are rendered according to the distances between curves generated from these points. Both methods provide a way to visually segment 2D cross sections of DTI data. Also, a particular contribution of the coloring technique used in our first visualization method is to give a continuous 2D color mapping that provides approximate perceptual uniformity and can be repeated an arbitrary number of times in both directions to increase sensitivity.

Sampling DTI fibers in the human brain based on DWI forward modeling

Abstract: We present a forward-modeling-based sampling of diffusion-tensor imaging (DTI) integral curves. This work has the potential to generate accurate brain neural fiber models that fit the data well with an economic number of curves. DTI integral curves are integrated from the first eigenvector field of the DTI field. Usually the seed points are generated randomly or from a regular grid in the data volume. The resulting set of integral curves are dense around the long and skinny neural fiber structures and sparse around the short and fat structures. There is currently a lack of quantitative indication of how well various models fit the data. We build a forward model that simulates diffusion-weighted images (DWIs) from the DTI integral curves based on a multi- tensor model. We employ the sum of the difference between the simulated DWIs and the acquired DWIs as the goal function and optimize the placement of the DTI integral curves with a greedy algorithm and a simulated annealing algorithm. The results show that with the same number of curves, the optimized set of DTI integral curves fit better to the data than randomly seeded integral curves. We extend the idea of image-guided streamline place- ment (9) to the DTI integral curves. We develop a forward model that generates DWIs from the integral curves with a multi-tensor model. We then use the difference between the simulated DWIs and acquired DWIs to guide the placement of the integral curves. A greedy algorithm and simulated annealing are used to optimize the configuration of the curves.

Perceptual coloring and 2D sketching for segmentation of neural pathways

Abstract: We present a system which visualizes the geometric disparity between white matter tracts obtained from DT-MRI by coloring in perceptually uniform color space and allows expert users of the application to select regions interactively with a 2D based sketching mechanism. This approach, in contrast to automatically clustering tracts, better reflects the uncertainity in forming scientific model from geometric information and the 2D sketching interface exploits neuroscientists' expertise with sectional anatomy.

P2-270: Diffusion-tensor imaging tractography: Correlation with processing speed in aging

Abstract: Table 1 provides descriptive statistics for the tractography and cognitive variables. Processing speed: There were trend level findings for step 1 (age, p = .079) and step 2 (TOIs, p = . 058). Age accounted for 28% of the variance in TMT-A performance (p =.079, trend). NTWL for the three TOIs accounted for an additional 41% of the variance (p = .101, trend for F change). Examination of standardized beta weights for the individual TOIs showed that NTWL in the right cingulum bundle was the strongest predictor (beta = − 585, p = .044 ; p > .05 for all other variables). Executive function: Step 1 was not significant (age, p = .46) and there was a trend level finding for step 2 (p = .08). Examination of standardized beta weights for the TOIs showed that NTWL in the interhemispheric fibers was the strongest predictor of TMT-B performance (beta = − .70, p = .01; p > .05 for all other variables). Conclusions