Jordan Ringenberg

Fast, accurate, and fully automatic segmentation of the right ventricle in short-axis cardiac MRI

This paper presents a fully automatic method to segment the right ventricle (RV) from short-axis cardiac MRI. A combination of a novel window-constrained accumulator thresholding technique, binary difference of Gaussian (DoG) filters, optimal thresholding, and morphology are utilized to drive the segmentation. A priori segmentation window constraints are incorporated to guide and refine the process, as well as to ensure appropriate area confinement of the segmentation. Training and testing were performed using a combined 48 patient datasets supplied by the organizers of the MICCAI 2012 right ventricle segmentation challenge, allowing for unbiased evaluations and benchmark comparisons. Marked improvements in speed and accuracy over the top existing methods are demonstrated.

Effects of Fibrosis Morphology on Reentrant Ventricular Tachycardia Inducibility and Simulation Fidelity in Patient-Derived Models

Myocardial fibrosis detected via delayed-enhanced magnetic resonance imaging (MRI) has been shown to be a strong indicator for ventricular tachycardia (VT) inducibility. However, little is known regarding how inducibility is affected by the details of the fibrosis extent, morphology, and border zone configuration. The objective of this article is to systematically study the arrhythmogenic effects of fibrosis geometry and extent, specifically on VT inducibility and maintenance. We present a set of methods for constructing patient-specific computational models of human ventricles using in vivo MRI data for patients suffering from hypertension, hypercholesterolemia, and chronic myocardial infarction. Additional synthesized models with morphologically varied extents of fibrosis and gray zone (GZ) distribution were derived to study the alterations in the arrhythmia induction and reentry patterns. Detailed electrophysiological simulations demonstrated that (1) VT morphology was highly dependent on the extent of fibrosis, which acts as a structural substrate, (2) reentry tended to be anchored to the fibrosis edges and showed transmural conduction of activations through narrow channels formed within fibrosis, and (3) increasing the extent of GZ within fibrosis tended to destabilize the structural reentry sites and aggravate the VT as compared to fibrotic regions of the same size and shape but with lower or no GZ. The approach and findings represent a significant step toward patient-specific cardiac modeling as a reliable tool for VT prediction and management of the patient. Sensitivities to approximation nuances in the modeling of structural pathology by image-based reconstruction techniques are also implicated.

Automated segmentation and reconstruction of patient-specific cardiac anatomy and pathology from in vivo MRI

This paper presents an automated method to segment left ventricle (LV) tissues from functional and delayed-enhancement (DE) cardiac magnetic resonance imaging (MRI) scans using a sequential multi-step approach. First, a region of interest (ROI) is computed to create a subvolume around the LV using morphological operations and image arithmetic. From the subvolume, the myocardial contours are automatically delineated using difference of Gaussians (DoG) filters and GSV snakes. These contours are used as a mask to identify pathological tissues, such as fibrosis or scar, within the DE-MRI. The presented automated technique is able to accurately delineate the myocardium and identify the pathological tissue in patient sets. The results were validated by two expert cardiologists, and in one set the automated results are quantitatively and qualitatively compared with expert manual delineation. Furthermore, the method is patient-specific, performed on an entire patient MRI series. Thus, in addition to providing a quick analysis of individual MRI scans, the fully automated segmentation method is used for effectively tagging regions in order to reconstruct computerized patient-specific 3D cardiac models. These models can then be used in electrophysiological studies and surgical strategy planning.

Evaluation and design of highly reliable and highly utilized cloud computing systems

Cloud computing paradigm has ushered in the need to provide resources to users in a scalable, flexible, and transparent fashion much like any other utility. This has led to a need for developing evaluation techniques that can provide quantitative measures of reliability of a cloud computing system (CCS) for efficient planning and expansion. This paper presents a new, scalable algorithm based on non-sequential Monte Carlo Simulation (MCS) to evaluate large scale cloud computing system (CCS) reliability, and it develops appropriate performance measures. Also, a new iterative algorithm is proposed and developed that leverages the MCS method for the design of highly reliable and highly utilized CCSs. The combination of these two algorithms allows CCSs to be evaluated by providers and users alike, providing a new method for estimating the parameters of service level agreements (SLAs) and designing CCSs to match those contractual requirements posed in SLAs. Results demonstrate that the proposed methods are effective and applicable to systems at a large scale. Multiple insights are also provided into the nature of CCS reliability and CCS design.

Accurate reconstruction of 3D cardiac geometry from coarsely-sliced MRI

We present a comprehensive validation analysis to assess the geometric impact of using coarsely-sliced short-axis images to reconstruct patient-specific cardiac geometry. The methods utilize high-resolution diffusion tensor MRI (DTMRI) datasets as reference geometries from which synthesized coarsely-sliced datasets simulating in vivo MRI were produced. 3D models are reconstructed from the coarse data using variational implicit surfaces through a commonly used modeling tool, CardioViz3D. The resulting geometries were then compared to the reference DTMRI models from which they were derived to analyze how well the synthesized geometries approximate the reference anatomy. Averaged over seven hearts, 95% spatial overlap, less than 3% volume variability, and normal-to-surface distance of 0.32 mm was observed between the synthesized myocardial geometries reconstructed from 8 mm sliced images and the reference data. The results provide strong supportive evidence to validate the hypothesis that coarsely-sliced MRI may be used to accurately reconstruct geometric ventricular models. Furthermore, the use of DTMRI for validation of in vivo MRI presents a novel benchmark procedure for studies which aim to substantiate their modeling and simulation methods using coarsely-sliced cardiac data. In addition, the paper outlines a suggested original procedure for deriving image-based ventricular models using the CardioViz3D software.

Applying the Norman 1986 User-Centered Model to Post-WIMP UIs: Theoretical Predictions and Empirical Outcomes

In recent decades, “post-WIMP” interactions have revolutionized user interfaces (UIs) and led to improved user experiences. However, accounts of post-WIMP UIs typically do not provide theoretical explanations of why these UIs lead to superior performance. In this article, we use Norman’s 1986 model of interaction to describe how post-WIMP UIs enhance users’ mental representations of UI and task. In addition, we present an empirical study of three UIs; in the study, participants completed a standard three-dimensional object manipulation task. We found that the post-WIMP UI condition led to enhancements of mental representation of UI and task. We conclude that the Norman model is a good theoretical framework to study post-WIMP UIs. In addition, by studying post-WIMP UIs in the context of the Norman model, we conclude that mental representation of task may be influenced by the interaction itself; this supposition is an extension of the original Norman model.

Interactive 3D Objects, Projections, and Touchscreens

It is widely recognized that features of objects in a user interface can impact aspects of user experience, including visual perception and problem solving. The current study looked at two such issues: 3D object projection and interactivity. Both factors are known to separately influence perception and problem solving; this work connected them together. Utilizing a fixed touchscreen user interface, we used two projections of 3D interactive cubes: oblique and parallel. The task was the Cube Comparison Task (CCT), a task known to be sensitive to both projection of 3D objects and interactivity. We measured the impact of projection of the interactive 3D objects on behaviors relating to alignment of object and environmental axes, foreshortening, and mapping of user interface controls. We also collected general performance measures of response time and accuracy in the CCT. We found minimal impact of projection of the interactive 3D objects on foreshortening, mapping of controls or general performance. However, we found that in both projections of interactive 3D objects, alignment between the object and environmental axes had a significant effect, leading to anisotropies in initial patterns of cube rotations. These anisotropies differed by projection. The results suggested that the manipulation of perceptual factors such as projection of interactive 3D objects can have effects on interactive problem solving, though the nuance of such effects may be influenced by additional factors. In particular, the interactive nature of our touchscreen user interface may have mitigated some effects that were otherwise predicted from prior research.