SCIENTIFIC COMPUTING AND IMAGING INSTITUTE
at the University of Utah

Created: 21 May 2012

Figure from R.S. MacLeod, et al., Subjectspecific, multiscale simulation of electrophysiology: a software pipeline for image-based models and application examples. Example A particle system provides adaptive sampling the various material boundaries of a segmented CT volume from a human torso.

Over the past year the CIBC, in partnership with our collaborators, has begun to introduce a generalized image-processing pipeline and associated software to the biomedical community.

With the widespread use of medical imaging, there is a growing need for better analysis of datasets. One method for improving analysis is to simulate biological processes and medical interventions in silico, in order to render better predictions. For example, the CIBC center is currently collaborating with Dr. Triedman at Children's Hospital in Boston to develop a computer model that will help guide the implantation of Implantable Cardiac Defibrillators (ICDs). This model uses pediatric imaging to select placement of electrode leads to generate the optimal field for defibrillation. One of the critical pieces in the development of the model is the generation of quality meshes for electric field simulation. Because the project is entering the validation phase where many cases need to be reviewed, a robust and automated Meshing Pipeline is required.

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Created: 21 May 2012

Atrial fibrillation (AF) is an electrophysiological condition that represents an increasing problem in the aging populations of the world; AF doubles the risk of stroke and mortality and diminishes quality of life. The best current method to evaluate the progression of AF and monitor the success of interventions is via an invasive intra-cardiac catheter-based electrical mapping procedure. A noninvasive means to evaluate characteristics of AF prior to treatment and to track the effect of interventions over time would be extremely valuable, and magnetic resonance imaging (MRI) offers such an opportunity. Before MRI can achieve its potential, there are challenging technical problems to overcome, such as the high spatial resolution required to image the thin atrial wall and the temporal resolution and gating necessary to compensate for the distorting effects of respiratory and cardiac motion. The Comprehensive Arrhythmia Research and Management (CARMA) Center has become a world leader in the use of MRI in AF and has overcome many of the image acquisition hurdles to make MRI a standard component of AF patient management at our institution. These improvements in image acquisition have opened up significant opportunities and new questions for the understanding and clinical management of AF.

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Created: 21 May 2012

An Isosurface visualization of a magnetic resonance imaging data set (in orange) surrounded by a volume rendered region of low opacity (in green) to indicate uncertainty in surface position.

The estimation and visualization of uncertainty information is an important research problem in both simulation and visualization. Uncertainty is a term used to describe the error, confidence, and variation of a dataset in order to allow a scientist to understand the accuracy not only of the data but also of the processes used to explore the data. One such technique, sensitivity analysis, helps the scientist to understand the effects of perturbing parameters of a function. Small perturbations of the input parameters that create large perturbations in the output results can indicate areas of the function that are highly dependent on the input parameters and may be interpreted as unstable or possibly wrong. Sensitivity analysis techniques can be used not only to explore the mathematical models used to generate uncertainty data but also to better understand the effects of input parameters of visualization techniques. Uncertainty data generated from the analysis of a mathematical model reconstructing biological experiment have been a focus of the CIBC team.

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Created: 10 December 2010

Atrial fibrillation (AF) is the most common—and perhaps most insidious—form of heart rhythm disturbance and treating it has become the focus of a group of bioengineers, imaging physicists, and physicians at the University of Utah.

In atrial fibrillation, the upper two chambers (the left and right atria) of the heart lose their synchronization and beat erratically and inefficiently. The same condition in the lower chambers (ventricles) of the heart is fatal within minutes and defibrillators are necessary to restore coordination. In the atria, death is by stealth and occurs over years, which is both good news and bad.

Because it is not immediately fatal, there is time to treat atrial fibrillation–but also time to ignore it. While it is not immediately life-threatening, AF does immediately reduce the pumping capacity of the heart and elevates the heart rate of the entire organ. Patients cannot be as physically active as they often wish but many adjust to the symptoms and live with the disease untreated for many years.

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Created: 27 July 2010

Figure from T. Fogal and J. Krüger, a Clearview rendering of the visible human male dataset

Attempting to display the entirety of a large volumetric dataset at one time would result in an overwhelming amount of information. Furthermore, visualization tools based on volume rendering present the user with a host of confusing options. We present ClearView, which provides a simplified volume visualization tool with a focus on doing what matters most: looking at your data. Users frequently want to direct the viewer's attention to a particular region of their volumes. With many volume rendering tools, this means setting up complex transfer functions to highlight the region of interest, with the unfortunate side effect of potentially affecting the larger image. ClearView allows the user to focus their visualization efforts on the area of their choice, while separating parameters for visualizing of surrounding data. This provides not only a simplified user interface, but finer-grained control over the final publication-quality visualization. Through advanced GPU rendering techniques, ClearView presents all of this to the user at highly interactive frame rates.

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Created: 26 July 2010

Figure from B.M. Issacson, et al., A unilateral hierarchical model was assembled as a representative image consisting of skin (purple) adipose tissue (yellow), musculature (pink), bone (blue), bone marrow (orange), and internal organs (green) (a). Each tissue type was assigned a specific conductivity using SCIRun. A large serpentine-like mass of HO was identified in the medial aspect of the residual limb, and was demonstrated in more detail in an axial cross section of the affected limb (b).

Osseointegration is a surgical procedure that provides direct skeletal attachment between an implant and host tissue with proven success in dental, auricle, and transfemoral implants. However, one challenge with using natural biological fixation is attaining a strong skeletal interlock at the implant interface, a prerequisite for long-term implant function. Utilizing metallic implants as a means of biological fixation has been the objective of orthopedic surgeons over the past two centuries. However, controlling osteogenesis at the implant interface, which is essential for providing strong skeletal fixation, remains challenging. Regulated electrical stimulation has proven effective in fracture healing and non-traumatized bone models, but has not been investigated in a percutaneous osseointegrated implant system. One advantage of the veteran patient population is that an orthopedic implant protrudes from the residual limb functioning as an exoprosthesis attachment and may operate as a potential cathode for an external electrical stimulation device.

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Created: 26 July 2010

A "typical" workflow that applies to many problems in biomedical simulation contains the  following elements: (i) Image acquisition and processing for a tissue, organ or region of interest (imaging and image processing), (ii) Identification of structures, tissues, cells or organelles within the images(image processing and segmentation), (iii) Fitting of geometric surfaces to the boundaries between structures and regions (geometric modelling), (iv) Generation of three-dimensional volume mesh from hexahedra or tetrahedra (meshing), and (v) Application of tissue parameters and boundary conditions and computation of spatial distribution of scalar, vector or tensor quantities of interest (simulation).

Over the past year the CIBC, in partnership with our collaborators, has begun to introduce a generalized processing pipeline and associated software to the biomedical community. This work has been largely influenced by DBP collaborators such as those collaborating to develop optimization strategies for ICD placement in children; Dr. John Triedman at the Department of Cardiology, Children's Hospital Boston, Dr. Matthew Jolley, Stanford University Medical Center. and Drs. Elizabeth Saarel, Tom Pilcher, and Michael Puchalski, all from the Department of Cardiology at Primary Childrens' Hospital in Salt Lake City. Additionally, collaborative work with the goal of the making osseointegrated amputee implants part of an electrical system to accelerate skeletal attachment also influenced the creation of the pipeline described below; collaborators are Brad Isaacson, Dr. Joseph Webster, Dr. James Beck, and Dr. Roy Bloebaum from the Department of Veteran Affairs and University of Utah.

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Created: 30 November 2012

Dr. Guido Gerig Early-Brain Development Research Reveals Vibrant Clues

By Peta Owens-Liston

Dr. Guido Gerig

The glossy whiteboards that line the walls in offices, lounge areas, and conference rooms are one of the first things Guido Gerig, PhD, noted when the University of Utah's Scientific Computing and Imaging (SCI) Institute first began courting him to join their team in 2007. For someone so prominent worldwide for his image analysis expertise and seminal research, whiteboards seemed the simplest of visual tools. Yet, what these signaled to Gerig was that this place fostered collaboration among students, postdocs, and faculty; these ubiquitous boards were an immediate means to visually improve understanding and share knowledge.

Pencil in hand, Gerig fills three pages with a whirl of sketches as he explains how his imaging work illuminates clinical findings in his research involving early brain development, and more specifically autism. The sketches fade to stick figure-status as Gerig jumps back and forth between the paper and the color-exploding images on his computer screen. Vivid and seemingly pulsating with life, the brain-development images are a result of thousands of highly precise, quantifiable measurements never before captured visually.

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Created: 14 March 2007

The Scientific Computing and Imaging Institute and the Musculoskeletal Research Laboratories are proud to announce the 1.0 release of the software FEBio, "Finite Elements for Biomechanics". FEBio is a nonlinear finite element software package that is specifically designed to address problems in computational biomechanics. Some of the features of note include capabilities for contact, rigid bodies and kinematic joints, nonlinear anisotropic constitutive models, simulation of active contraction, poroelasticity, element formulations for nearly-incompressible materials and parallel solution of the linear system of equations. After extensive testing in our lab and with our collaborators, we are happy to offer this free software to the research community. FEBio is currently available for WindowsXP, MacOS/X, Suse Linux (64 bit Opteron/Athlon64) and SGI Altix (64 bit Itanium2). We would be happy to port FEBio to other Unix/Linux platforms. The FEBio distribution includes the User's Manual, Theory Manual and several test problems to verify proper operation.

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Created: 01 September 2004

Associate Professor Ross Whitaker and Assistant Professor David Breen (Drexel University) have been developing surface modeling techniques based on level sets. These techniques include efficient algorithms for representing level-set surfaces and a new formulation for deforming one 3D object into another (also called 3D morphing). This combination of technologies provides an easy and efficient way to smoothly transform any 3D object to the shape of a target form. Recently, these methods were adopted by the special effects gurus at Frantic Films to create stunning visual effects for the movie Scooby-Doo 2.

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