Center for Integrative Biomedical Computing

SCI Publications


D. Perry, A. Morris, N. Burgon, C. McGann, R.S. MacLeod, J. Cates. “Automatic classification of scar tissue in late gadolinium enhancement cardiac MRI for the assessment of left-atrial wall injury after radiofrequency ablation,” In SPIE Proceedings, Vol. 8315, pp. (published online). 2012.
DOI: 10.1117/12.910833
PubMed ID: 24236224
PubMed Central ID: PMC3824273


Radiofrequency ablation is a promising procedure for treating atrial fibrillation (AF) that relies on accurate lesion delivery in the left atrial (LA) wall for success. Late Gadolinium Enhancement MRI (LGE MRI) at three months post-ablation has proven effective for noninvasive assessment of the location and extent of scar formation, which are important factors for predicting patient outcome and planning of redo ablation procedures. We have developed an algorithm for automatic classification in LGE MRI of scar tissue in the LA wall and have evaluated accuracy and consistency compared to manual scar classifications by expert observers. Our approach clusters voxels based on normalized intensity and was chosen through a systematic comparison of the performance of multivariate clustering on many combinations of image texture. Algorithm performance was determined by overlap with ground truth, using multiple overlap measures, and the accuracy of the estimation of the total amount of scar in the LA. Ground truth was determined using the STAPLE algorithm, which produces a probabilistic estimate of the true scar classification from multiple expert manual segmentations. Evaluation of the ground truth data set was based on both inter- and intra-observer agreement, with variation among expert classifiers indicating the difficulty of scar classification for a given a dataset. Our proposed automatic scar classification algorithm performs well for both scar localization and estimation of scar volume: for ground truth datasets considered easy, variability from the ground truth was low; for those considered difficult, variability from ground truth was on par with the variability across experts.

K. Potter, R.M. Kirby, D. Xiu, C.R. Johnson. “Interactive visualization of probability and cumulative density functions,” In International Journal of Uncertainty Quantification, Vol. 2, No. 4, pp. 397--412. 2012.
DOI: 10.1615/Int.J.UncertaintyQuantification.2012004074
PubMed ID: 23543120
PubMed Central ID: PMC3609671


The probability density function (PDF), and its corresponding cumulative density function (CDF), provide direct statistical insight into the characterization of a random process or field. Typically displayed as a histogram, one can infer probabilities of the occurrence of particular events. When examining a field over some two-dimensional domain in which at each point a PDF of the function values is available, it is challenging to assess the global (stochastic) features present within the field. In this paper, we present a visualization system that allows the user to examine two-dimensional data sets in which PDF (or CDF) information is available at any position within the domain. The tool provides a contour display showing the normed difference between the PDFs and an ansatz PDF selected by the user, and furthermore allows the user to interactively examine the PDF at any particular position. Canonical examples of the tool are provided to help guide the reader into the mapping of stochastic information to visual cues along with a description of the use of the tool for examining data generated from a uncertainty quantification exercise accomplished within the field of electrophysiology.

Keywords: visualization, probability density function, cumulative density function, generalized polynomial chaos, stochastic Galerkin methods, stochastic collocation methods

K. Potter, P. Rosen, C.R. Johnson. “From Quantification to Visualization: A Taxonomy of Uncertainty Visualization Approaches,” In Uncertainty Quantification in Scientific Computing, IFIP Advances in Information and Communication Technology Series, Vol. 377, Edited by Andrew Dienstfrey and Ronald Boisvert, Springer, pp. 226--249. 2012.
DOI: 10.1007/978-3-642-32677-6_15


Quantifying uncertainty is an increasingly important topic across many domains. The uncertainties present in data come with many diverse representations having originated from a wide variety of domains. Communicating these uncertainties is a task often left to visualization without clear connection between the quantification and visualization. In this paper, we first identify frequently occurring types of uncertainty. Second, we connect those uncertainty representations to ones commonly used in visualization. We then look at various approaches to visualizing this uncertainty by partitioning the work based on the dimensionality of the data and the dimensionality of the uncertainty. We also discuss noteworthy exceptions to our taxonomy along with future research directions for the uncertainty visualization community.

Keywords: scidac, netl, uncertainty visualization

M.W. Prastawa, S.P. Awate, G. Gerig. “Building Spatiotemporal Anatomical Models using Joint 4-D Segmentation, Registration, and Subject-Speci fic Atlas Estimation,” In Proceedings of the 2012 IEEE Mathematical Methods in Biomedical Image Analysis (MMBIA) Conference, pp. 49--56. 2012.
DOI: 10.1109/MMBIA.2012.6164740
PubMed ID: 23568185
PubMed Central ID: PMC3615562


Longitudinal analysis of anatomical changes is a vital component in many personalized-medicine applications for predicting disease onset, determining growth/atrophy patterns, evaluating disease progression, and monitoring recovery. Estimating anatomical changes in longitudinal studies, especially through magnetic resonance (MR) images, is challenging because of temporal variability in shape (e.g. from growth/atrophy) and appearance (e.g. due to imaging parameters and tissue properties affecting intensity contrast, or from scanner calibration). This paper proposes a novel mathematical framework for constructing subject-specific longitudinal anatomical models. The proposed method solves a generalized problem of joint segmentation, registration, and subject-specific atlas building, which involves not just two images, but an entire longitudinal image sequence. The proposed framework describes a novel approach that integrates fundamental principles that underpin methods for image segmentation, image registration, and atlas construction. This paper presents evaluation on simulated longitudinal data and on clinical longitudinal brain MRI data. The results demonstrate that the proposed framework effectively integrates information from 4-D spatiotemporal data to generate spatiotemporal models that allow analysis of anatomical changes over time.

Keywords: namic, adni, autism

R. Ranjan, E.G. Kholmovski, J. Blauer, S. Vijayakumar, N.A. Volland, M.E. Salama, D.L. Parker, R.S. MacLeod, N.F. Marrouche. “Identification and Acute Targeting of Gaps in Atrial Ablation Lesion Sets Using a Real-Time Magnetic Resonance Imaging System,” In Circulation: Arrhythmia and Electrophysiology, Vol. 5, pp. 1130--1135. 2012.
DOI: 10.1161/CIRCEP.112.973164
PubMed ID: 23071143
PubMed Central ID: PMC3691079


Background - Radiofrequency ablation is routinely used to treat cardiac arrhythmias, but gaps remain in ablation lesion sets because there is no direct visualization of ablation-related changes. In this study, we acutely identify and target gaps using a real-time magnetic resonance imaging (RT-MRI) system, leading to a complete and transmural ablation in the atrium.

Methods and Results - A swine model was used for these studies (n=12). Ablation lesions with a gap were created in the atrium using fluoroscopy and an electroanatomic system in the first group (n=5). The animal was then moved to a 3-tesla MRI system where high-resolution late gadolinium enhancement MRI was used to identify the gap. Using an RT-MRI catheter navigation and visualization system, the gap area was ablated in the MR scanner. In a second group (n=7), ablation lesions with varying gaps in between were created under RT-MRI guidance, and gap lengths determined using late gadolinium enhancement MR images were correlated with gap length measured from gross pathology. Gaps up to 1.0 mm were identified using gross pathology, and gaps up to 1.4 mm were identified using late gadolinium enhancement MRI. Using an RT-MRI system with active catheter navigation gaps can be targeted acutely, leading to lesion sets with no gaps. The correlation coefficient (R2) between the gap length was identified using MRI, and the gross pathology was 0.95.

Conclusions - RT-MRI system can be used to identify and acutely target gaps in atrial ablation lesion sets. Acute targeting of gaps in ablation lesion sets can potentially lead to significant improvement in clinical outcomes.

P. Rosen, V. Popescu. “Simplification of Node Position Data for Interactive Visualization of Dynamic Datasets,” In IEEE Transactions on Visualization and Computer Graphics (IEEE Visweek 2012 TVCG Track), pp. 1537--1548. 2012.
PubMed ID: 22025753
PubMed Central ID: PMC3411892


We propose to aid the interactive visualization of time-varying spatial datasets by simplifying node position data over the entire simulation as opposed to over individual states. Our approach is based on two observations. The first observation is that the trajectory of some nodes can be approximated well without recording the position of the node for every state. The second observation is that there are groups of nodes whose motion from one state to the next can be approximated well with a single transformation. We present dataset simplification techniques that take advantage of this node data redundancy. Our techniques are general, supporting many types of simulations, they achieve good compression factors, and they allow rigorous control of the maximum node position approximation error. We demonstrate our approach in the context of finite element analysis data, of liquid flow simulation data, and of fusion simulation data.

P. Rosen. “Rectilinear Texture Warping for Fast Adaptive Shadow Mapping,” In Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (I3D '12), pp. 151--158. 2012.


Conventional shadow mapping relies on uniform sampling for producing hard shadow in an efficient manner. This approach trades image quality in favor of efficiency. A number of approaches improve upon shadow mapping by combining multiple shadow maps or using complex data structures to produce shadow maps with multiple resolutions. By sacrificing some performance, these adaptive methods produce shadows that closely match ground truth.

This paper introduces Rectilinear Texture Warping (RTW) for efficiently generating adaptive shadow maps. RTW images combine the advantages of conventional shadow mapping - a single shadow map, quick construction, and constant time pixel shadow tests, with the primary advantage of adaptive techniques - shadow map resolutions which more closely match those requested by output images. RTW images consist of a conventional texture paired with two 1-D warping maps that form a rectilinear grid defining the variation in sampling rate. The quality of shadows produced with RTW shadow maps of standard resolutions, i.e. 2,048×2,048 texture for 1080p output images, approaches that of raytraced results while low overhead permits rendering at hundreds of frames per second.

Keywords: Rendering, Shadow Algorithms, Adaptive Sampling

L. Zhu, Y. Gao, A. Yezzi, R.S. MacLeod, J. Cates, A. Tannenbaum. “Automatic Segmentation of the Left Atrium from MRI Images using Salient Feature and Contour Evolution,” In Proceedings of the 34th Annual International Conference of the IEEE EMBS, pp. 3211--214. 2012.
DOI: 10.1109/EMBC.2012.6346648
PubMed ID: 23366609
PubMed Central ID: PMC3652873


We propose an automatic approach for segmenting the left atrium from MRI images. In particular, the thoracic aorta is detected and used as a salient feature to find a seed region that lies inside the left atrium. A hybrid energy that combines robust statistics and localized region intensity information is employed to evolve active contours from the seed region to capture the whole left atrium. The experimental results demonstrate the accuracy and robustness of our approach.


N. Akoum, M. Daccarett, C. McGann, N. Segerson, G. Vergara, S. Kuppahally, T. Badger, N. Burgon, T. Haslam, E. Kholmovski, R.S. MacLeod, N.F. Marrouche. “Atrial fibrosis helps select the appropriate patient and strategy in catheter ablation of atrial fibrillation: a DE-MRI guided approach,” In Journal of Cardiovascular Electrophysiology, Vol. 22, No. 1, pp. 16--22. 2011.
DOI: 10.1111/j.1540-8167.2010.01876.x
PubMed ID: 20807271


Atrial fibrillation (AF) is the most common sustained arrhythmia encountered in adult cardiology.1,2 Several studies have demonstrated that AF is associated with electrical, contractile, and structural remodeling (SRM) in the left atrium (LA) that contributes to the persistence and sustainability of the arrhythmia.3-7 It has also been shown that the end result of this remodeling process is loss of atrial myocytes and increased collagen content and hence fibrosis of the LA wall.5 Delayed enhancement MRI (DE-MRI) using gadolinium contrast has been demonstrated to localize and quantify the degree of SRM or fibrosis associated with AF in the LA.8

DE-MRI has also been shown to be useful in localizing and quantifying scar formation in the LA following radiofrequency ablation (RFA).9,10 The pulmonary vein (PV) antral region can be visualized to assess circumferential PV scarring that results from RFA lesions/ablation. In addition, the amount of scarring to the LA after catheter ablation can be quantified as a proportion of the total left atrial volume.

Rhythm control of AF using catheter ablation has yielded varying results in different patient populations.11 Identifying the ideal candidate for catheter ablation remains a significant challenge. In addition, a number of different approaches to catheter ablation have been reported and most experts agree that 1 ablation strategy does not fit allAF patients.11-15 Therefore, selecting the proper strategy for a particular patient is also an important determinant of procedure success.

We used DE-MRI to quantify both the degree of SRM/fibrosis pre-ablation and scar formation post ablation. Our aim was to identify predictors of successful ablation in a group of patients stratified according to pre-ablation fibrosis. This would help select the most appropriate ablation strategy for the individual AF ablation candidate.

N. Andrysco, P. Rosen, V. Popescu, B. Benes, K.R. Gurney. “Experiences in Disseminating Educational Visualizations,” In Lecture Notes in Computer Science (7th International Symposium on Visual Computing), Vol. 2, pp. 239--248. September, 2011.
DOI: 10.1007/978-3-642-24031-7_24


Most visualizations produced in academia or industry have a specific niche audience that is well versed in either the often complicated visualization methods or the scientific domain of the data. Sometimes it is useful to produce visualizations that can communicate results to a broad audience that will not have the domain specific knowledge often needed to understand the results. In this work, we present our experiences in disseminating the results of two studies to national audience. The resulting visualizations and press releases allowed the studies’ researchers to educate a national, if not global, audience.

B.M. Burton, J.D. Tate, B. Erem, D.J. Swenson, D.F. Wang, D.H. Brooks, P.M. van Dam, R.S. MacLeod. “A Toolkit for Forward/Inverse Problems in Electrocardiography within the SCIRun Problem Solving Environment,” In Proceedings of the 2011 IEEE Int. Conf. Engineering and Biology Society (EMBC), pp. 267--270. 2011.
DOI: 10.1109/IEMBS.2011.6090052
PubMed ID: 22254301
PubMed Central ID: PMC3337752


Computational modeling in electrocardiography often requires the examination of cardiac forward and inverse problems in order to non-invasively analyze physiological events that are otherwise inaccessible or unethical to explore. The study of these models can be performed in the open-source SCIRun problem solving environment developed at the Center for Integrative Biomedical Computing (CIBC). A new toolkit within SCIRun provides researchers with essential frameworks for constructing and manipulating electrocardiographic forward and inverse models in a highly efficient and interactive way. The toolkit contains sample networks, tutorials and documentation which direct users through SCIRun-specific approaches in the assembly and execution of these specific problems.

A.N.M. Imroz Choudhury, P. Rosen. “Abstract Visualization of Runtime Memory Behavior,” In 6th IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT 2011), pp. 22--29. 2011.


We present a system for visualizing memory reference traces, the records of the memory transactions performed by a program at runtime. The visualization consists of a structured layout representing the levels of a cache and a set of data glyphs representing the pieces of data in memory being operated on during application runtime. The data glyphs move in response to events generated by a cache simulator, indicating their changing residency in the various levels of the memory hierarchy. Within the levels, the glyphs arrange themselves into higher-order shapes representing the structure of the cache levels, including the composition of their associative cache sets and eviction ordering. We make careful use of different visual channels, including structure, motion, color, and size, to convey salient events as they occur. Our abstract visualization provides a high-level, global view of memory behavior, while giving insight about important events that may help students or software engineers to better understand their software’s performance and behavior.

M. Daccarett, T.J. Badger, N. Akoum, N.S. Burgon, C. Mahnkopf, G.R. Vergara, E.G. Kholmovski, C.J. McGann, D.L. Parker, J. Brachmann, R.S. Macleod, N.F. Marrouche. “Association of left atrial fibrosis detected by delayed-enhancement magnetic resonance imaging and the risk of stroke in patients with atrial fibrillation,” In Journal of the American College of Cardiology, Vol. 57, No. 7, pp. 831--838. 2011.
PubMed ID: 21310320

M. Daccarett, C.J. McGann, N.W. Akoum, R.S. MacLeod, N.F. Marrouche. “MRI of the left atrium: predicting clinical outcomes in patients with atrial fibrillation,” In Expert Review of Cardiovascular Therapy, Vol. 9, No. 1, pp. 105--111. 2011.
PubMed ID: 21166532

M. Datar, Y. Gur, B. Paniagua, M. Styner, R.T. Whitaker. “Geometric Correspondence for Ensembles of Nonregular Shapes,” In Proceedings of Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), Lecture Notes in Computer Science (LNCS), Vol. 6892, pp. 368--375. 2011.
DOI: 10.1007/978-3-642-23629-7_45
PubMed ID: 21995050
PubMed Central ID: PMC3346950


An ensemble of biological shapes can be represented and analyzed with a dense set of point correspondences. In previous work, optimal point placement was determined by optimizing an information theoretic criterion that depends on relative spatial locations on different shapes combined with pairwise Euclidean distances between nearby points on the same shape. These choices have prevented such methods from effectively characterizing shapes with complex geometry such as thin or highly curved features. This paper extends previous methods for automatic shape correspondence by taking into account the underlying geometry of individual shapes. This is done by replacing the Euclidean distance for intrashape pairwise particle interactions by the geodesic distance. A novel set of numerical techniques for fast distance computations on curved surfaces is used to extract these distances. In addition, we introduce an intershape penalty term that incorporates surface normal information to achieve better particle correspondences near sharp features. Finally, we demonstrate this new method on synthetic and biological datasets.

Keywords: namic

B. Erem, D.H. Brooks, P.M. van Dam, J.G. Stinstra, R.S. MacLeod. “Spatiotemporal Estimation of Activation Times of Fractionated ECGs on Complex Heart Surfaces,” In Proceedings of the International Coference of the IEEE Engineering in Medicine and Biology Society (EMBS), pp. 5884--5887. 2011.
DOI: 10.1109/IEMBS.2011.6091455
PubMed ID: 22255678
PubMed Central ID: PMC3345888


Identification of electrical activation or depolarization times on sparsely-sampled complex heart surfaces is of importance to clinicians and researchers in cardiac electrophysiology. We introduce a spatiotemporal approach for activation time estimation which combines prior results using spatial and temporal methods with our own progress on gradient estimation on triangulated surfaces. Results of the method applied to simulated and canine heart data suggest that improvements are possible using this novel combined approach.

B. Erem, P.M. van Dam, D.H. Brooks. “Analysis of the Criteria of Activation-Based Inverse Electrocardiography using Convex Optimization,” In Conf Proc IEEE Eng Med Biol Soc, pp. 3913–3916. 2011.
DOI: 10.1109/IEMBS.2011.6090972
PubMed ID: 22255195
PubMed Central ID: PMC3359386


In inverse electrocardiography (ECG), the problem of finding activation times on the heart noninvasively from body surface potentials is typically formulated as a nonlinear least squares optimization problem. Current solutions rely on iterative algorithms which are sensitive to the presence of local minima. As a result, improved initialization approaches for this problem have been of considerable interest. However, in experiments conducted on a subject with Wolff-Parkinson-White syndrome, we have observed that there may be a mismatch between favorable solutions of the optimization problem and solutions with the desired physiological characteristics. In this work, we use a method based on a convex optimization framework to explore the solution space and analyze whether the optimization criteria target their intended objective.

B. Erem, D.H. Brooks. “Differential Geometric Approximation of the Gradient and Hessian on a Triangulated Manifold,” In Proceeding of the IEEE International Symposium on Biomedical Imaging: from nano to macro, pp. 504--507. 2011.
DOI: 10.1109/ISBI.2011.5872455
PubMed ID: 21712967
PubMed Central ID: PMC3122924


In a number of medical imaging modalities, including measurements or estimates of electrical activity on cortical or cardiac surfaces, it is often useful to estimate spatial derivatives of data on curved anatomical surfaces represented by triangulated meshes. Assuming the triangle vertices are points on a smooth manifold, we derive a method for estimating gradients and Hessians on locally 2D surfaces embedded in 3D directly in the global coordinate system. Accuracy of the method is validated through simulations on both smooth and corrugated surfaces.

T. Fogal, J. Krüger. “Efficient I/O for Parallel Visualization,” In Proceedings of the Eurographics Symposium on Parallel Graphics and Visualization (2011), Edited by T. Kuhlen and R. Pajarola and K. Zhou, pp. 81--90. 2011.

Z. Fu, W.-K. Jeong, Y. Pan, R.M. Kirby, R.T. Whitaker. “A fast iterative method for solving the Eikonal equation on triangulated surfaces,” In SIAM Journal of Scientific Computing, Vol. 33, No. 5, pp. 2468--2488. 2011.
DOI: 10.1137/100788951
PubMed Central ID: PMC3360588


This paper presents an efficient, fine-grained parallel algorithm for solving the Eikonal equation on triangular meshes. The Eikonal equation, and the broader class of Hamilton–Jacobi equations to which it belongs, have a wide range of applications from geometric optics and seismology to biological modeling and analysis of geometry and images. The ability to solve such equations accurately and efficiently provides new capabilities for exploring and visualizing parameter spaces and for solving inverse problems that rely on such equations in the forward model. Efficient solvers on state-of-the-art, parallel architectures require new algorithms that are not, in many cases, optimal, but are better suited to synchronous updates of the solution. In previous work [W. K. Jeong and R. T. Whitaker, SIAM J. Sci. Comput., 30 (2008), pp. 2512–2534], the authors proposed the fast iterative method (FIM) to efficiently solve the Eikonal equation on regular grids. In this paper we extend the fast iterative method to solve Eikonal equations efficiently on triangulated domains on the CPU and on parallel architectures, including graphics processors. We propose a new local update scheme that provides solutions of first-order accuracy for both architectures. We also propose a novel triangle-based update scheme and its corresponding data structure for efficient irregular data mapping to parallel single-instruction multiple-data (SIMD) processors. We provide detailed descriptions of the implementations on a single CPU, a multicore CPU with shared memory, and SIMD architectures with comparative results against state-of-the-art Eikonal solvers.