Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.
SCIRun is the integrated programming environment that has been a core technology of the CIBC since its inception and each major version release is an enormous undertaking. The program now contains hundreds of thousands of lines of C++ code and a new release requires at least a review of all this code, with replacement or updating of larger portions of it. We are nearing the first release of such a major new version, SCIRun 5.

There must be considerable motivation for such a major release, motivation which comes from both our users, collaborators, and DBP partners but also from advances in software engineering and scientific computing, with which we must also keep pace. Our users continue to demand more efficiency, more flexibility in programming the workflows created with SCIRun, more support for big data, and more transparent access to large compute resources when simulations exceed the useful capacity of local resources. The evolution of software engineering has led to changes in computer languages, programming paradigms, visualization hardware and processing, user interface design (and tools to support this critical component), and the third party libraries that form the building blocks of complex scientific software. SCIRun 5 is a response to all these changing conditions and needs and also represents some long awaited refactoring that will provide greater flexibility and freedom as we move into the next generation of scientific computing.

Figure 1: 3D surface mesh of a face.
Partial differential equations (PDEs) are ubiquitous in engineering applications. They mathematically model natural phenomena such as heat conduction, diffusion, and shock wave propagation. They also describe many bioelectrical and biomechanical functions and are a central element of the simulation research of the Center. Analytical solutions for most PDEs are known only for certain symmetric domains, such as a circle, square, or sphere. In order to obtain solutions to PDEs for more realistic domains, numerical approximations such as the finite element method (FEM) are used. In the FEM, both the domain and the PDE are discretized and a numerical solution is calculated using computational resources. The discretization of the geometric domain is called a mesh. Meshes play a vital role in the numerical solution of PDEs on a given geometric domain, the accuracy of which depends on parameters such as the shape and size of the mesh elements. The most commonly used meshes contain tetrahedral elements. While simple conceptually, mesh generation is one of the most computationally intensive tasks in solving a PDE numerically.

visoarIntroducing ViSOAR. As data acquisition advances, and data sizes increase, the need for tools to process and visualize the results in an effective and efficient manner is becoming increasingly important. The reliance on supercomputers for scientific visualization and analysis is already proving to be a hindrance for wide accessibility to researchers and scientists dealing with large data.

The Scientific Computing and Imaging (SCI) Institute and the Center for Extreme Data Management, Analysis, and Visualization (CEDMAV), in collaboration with ARUP Laboratories and the University of Utah, Department of Neurobiology and Anatomy, have developed ViSOAR--a multi platform visualization application for accessing and processing very large imaging data.

EEGfig2In collaboration with Dr. Don Tucker and his colleagues at Electrical Geodesics Inc (EGI) and the University of Oregon, this DBP is concerned with improving our ability to reconstruct and visualize neuroelectric sources (source localization) from EEG measurements and also our ability to stimulate specific brain regions using electrodes attached on to the scalp of the subject (transcranial direct current stimulation, tDCS).

For both research and clinical practice, EEG is a cost-effective tool to understand and excite brain activity. EEG advances have significantly improved the spatial resolution of source estimates and offer the promise of precise spatio-temporal monitoring and stimulation of cortical brain activity. By itself, high-resolution EEG would be affordable even for small hospitals in remote locations and could be easily managed by technicians in the field.

Femoroacetabular impingement (FAI) is caused by reduced clearance between the femoral head and acetabulum due to anatomic abnormalities of the femur (cam FAI), acetabulum (pincer FAI), or both (mixed FAI). Cam FAI is characterized by an aspherical femoral head or reduced femoral head-neck offset. During hip flexion, the abnormally shaped femur may cause shearing at the chondrolabral junction, thereby damaging articular cartilage and the acetabular labrum. Currently, diagnosis of cam FAI is largely accomplished using two-dimensional (2D) measurements of femur morphology acquired from radiographic projections or a series of radial planes from computed tomography (CT) or magnetic resonance (MR) images. Two- dimensional measures provide initial diagnosis of cam FAI, but their reliability has been debated. Also, there is no agreement on the range of measurements that should be considered normal. Furthermore, radiographic measures give only a limited description of femur anatomy or shape variation among cam FAI deformities. Together, these limitations of 2D measurements translate into a high misdiagnosis rate. In a series of FAI patients treated with surgery in our clinic, 40% had seen multiple previous musculoskeletal providers and 15% had undergone surgical procedures unrelated to the hip joint (hernia, etc.).

Mean control (left) and cam (right) shapes. Middle images show the mean control shape with color plots depicting how the mean cam shape differed across the femoral head, neck, and proximal shaft. Top and bottom rows show different rotations of the femoral head. Volumetric CT images from a cam FAI patient. Validated threshold settings were applied to CT images to segment and reconstruct the bony morphology of each femur.

Corview screenshot
Atrial fibrillation (AF) is a cardiac rhythm disturbance in which the atria, the upper chambers of the heart, undergo uncontrolled and uncoordinated electrical activation so that contraction of the atria contributes almost nothing to cardiac output. While not immediately atal (as is ventricular fibrillation) AF dramatically increases the risk of stroke, elevates mortality, and diminishes quality of life. Traditional diagnosis of AF as been limited to ECG-based determination of the time spent in this arrhythmia and there has previously been no other dependable biomarker capable of determining either the progression of the disease or of determining suitable treatment approaches. Therapy for AF consists of either antiarrhythmic drugs that may control the arrhythmia completely or at least reduce the resulting elevated heart rate combined with anticoagulation therapy or ablation. Ablation involves destroying targeted regions of the atria with the goal of either isolated triggers of spurious electrical activity or functionally separating the atrial wall into small enough segments that the putative mechanism of the arrhythmia cannot longer sustain. The latter approach is a form of substrate stabilization, and the management of this disease has suffered from a persistent lack of means to monitor or evaluate the stability of the tissue. It is precisely in this aspect that cardiologist at the University of Utah, with support from the CIBC have made their most significant contributions.

An interdisciplinary team at the Comprehensive Arrhythmia and MAnagement (CARMA) Center have made use of the segmentation, image analysis, and recently mesh generation and simulation capabilities of the CIBC to create a comprehensive program for AF management. The scope of the progress continues to expand each year and this application of CIBC technology has proven very fruitful even as it is very challenging.

DBS figure
Overview of the DBS system. The DBS electrode is implanted in the brain during stereotactic surgery. The electrode is attached via an extension wire to the IPG, which is implanted in the torso. The entire system is subcutaneous and is designed to deliver continuous stimulation for several years at a time.
In recent years, there has been significant growth in the use of patient-specific models to predict the effects of neuromodulation therapies, such as deep brain stimulation (DBS). However, translating these models from a research environment to the everyday clinical workflow is a challenge, primarily due to the complexity of the models and the expertise required in specialized visualization software. Recently, the CIBC has worked with Dr. Christopher Butson at the University of Wisconsin to deploy the interactive visualization system ImageVis3D Mobile for experimental use in the area of DBS planning. In addition to running on multi-node compute clusters and large desktop systems, ImageVis3D is also designed for mobile computing devices such as the iPhone or iPad. In this case, ImageVis3D was modified for an evaluation environment in order to visualize models of Parkinson's Disease (PD) patients who received DBS therapy1.

The selection of DBS settings is a significant clinical challenge that requires repeated revisions to achieve optimal therapeutic response, and is often performed without any visual representation of the stimulation system in the patient. We used ImageVis3D Mobile to provide models to movement disorders clinicians and asked them to use the software to determine: 1) which of the four DBS electrode contacts they would select for therapy and 2) what stimulation settings they would choose. We compared the stimulation protocol chosen from the software versus the stimulation protocol that was chosen via clinical practice (independent of the study). Lastly, we compared the amount of time required to reach these settings using the software versus the time required through standard practice. We found that the stimulation settings chosen using ImageVis3D Mobile were similar to those used in standard care, but were selected in drastically less time. We found that our visualization system, available directly at the point of care on a device familiar to the clinician, can be used to guide clinical decision-making for selecting DBS settings. The positive impact of the system could also translate to areas other than DBS.

Torso stuff
A cross-section of a 3-dimensional, tetrahedral mesh of a torso. Each separate organ type is shown using a different color.
This year, an essential goal has been to enhance the generalized image-processing pipeline of software developed by CIBC and its partners. With the growing use of high quality medical imaging, practitioners around the globe are employing these acquired datasets for performing biomedical simulation. In its holistic approach to image-to-simulation pipelines, our software starts with image data and processing, constructs geometric models, performs simulation, and provides biophysical analysis of the data. A research highlight for the CIBC this year is the development of an improved scheme for mesh generation, a critical step within this pipeline. This research complements the software package BioMesh3D, but targets a completely different niche in the world of mesh generation algorithms.

High Quality Meshing

The problem of mesh generation has been widely studied, as a hybrid field of interest to the scientific, engineering, and computer science communities. In each of these fields, meshes are used to compute numerical approximations to solutions of partial differential equations. To do so, continuous mathematics are replaced with a discrete analogue, most commonly to facilitate the finite element method (FEM).

The FEM works by decomposing a domain of interest into discrete entities of various dimensions, such as points (0-dimensional), edges (1-dimensional), and cells of higher dimension (frequently triangles and quadrilaterals are used for 2-dimensionl elements, tetrahedra and hexahedra for 3-dimensional). Together, these elements form what is commonly called a mesh (see figure)Solutions to the complex system are solved piecewise on each element, and then aggregated together to form the final solution. The FEM has become an important tool in medical imaging as well. For example, CT scans of legs can be meshed so that orthopedic modeling can accurately simulate gait, MRI scans of the torso are frequently used in cardiac electrophysical modeling, and images of the skull can identify structures of the brain.

Because the FEM is a computational tool that processes individual elements to approximate a whole solution, it is deeply impacted by the mesh elements used to represent the space. Two principle concerns stand out in the meshing problem for medical images:

For years, a central focus of the Center for Integrative Biomedical Computing has been software dissemination. Over the Center's twelve-year history, the infrastructure of CIBC's software dissemination efforts have undergone a radical evolution, with many lessons learned for both users and developers.

Software Dissemination as a Form of Science and Technology Dissemination

scirun 1
The SCIRun/BioPSE Problem-Solving Environment. This system was designed as a 'computational workbench' and represented a new approach to bringing high-end computational tools to the biomedical researcher.
From the outset, the Center's leadership believed that along with the typical avenues of dissemination, publications, seminars, workshops, conference presentations, etc.‚ software dissemination held a particularly high potential as a means to disseminate the knowledge and advances of the Center and its collaborators. This fundamental belief led to experimentation in a variety of topics, such as software licensing, open source repositories, make systems, operating systems, source code/binary releases, research code versus releasable code, software support, and release schedules.

The origins of our success in developing widely used software tools lie in a set of strategies for algorithm research and software development. One such strategy is the production of software tools with low barriers to entry. This entails the release of documented, tested, complete applications that do not require learning new programming languages or complex, architecture-specific build environments. We also continue to follow an initiative to create a suite of lightweight, stand-alone applications, directed at specific tasks of common interest across a wide set of disciplines. The result is a set of programs, such as Seg3D, with large and growing user bases.

iv3dThe SCI Institute holds a strong belief that providing research opportunities to undergraduate and even high school students will not only encourage them to pursue studies in the sciences, but also give them a head start in their future academic lives. Being allowed to work side by side with PhD-level scientists within a real research institute moves science from something that happens in a text book or highly structured laboratory to the dynamic work environment shared by scientists around the world.

In this year's high school summer intern program, the SCI Institute invited four students, one each from Juan Diego Catholic High School, The Waterford School, and two from West High School. These students were given the opportunity to work with a lead software developer from the National Institutes of Health (NIH) sponsored Center for Integrative Biomedical Computing (CIBC). Their task seemed simple: take Seg3D and ImageVis3D (two advanced software tools developed by the CIBC), find a dataset of interest to the student, load that data, and experiment with the software on both desktop and iPad versions. And then, present your results to your high school peers. In the end, the students learned that research is a full-contact sport, not just a homework assignment. They had to 'dig-in', expand their knowledge, and learn about their subjects of interest, their data, their software, even their computers. In the end, the students translated this process and knowledge to science classes at their school. And, the top question after the presentations? Oddly enough, "how do I get an internship like yours?" Kids excited about a science internship! Mission Accomplished.

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.

by Gregory Scott Jones - NICS

The crater resulting from the Spanish Fork Detonation.
First, the bad news: all across America, trucks and tractor-trailers are transporting industrial explosives on nearly every artery of the country's interstate and highway system. That's right, volatile explosives, including munitions, rocket motors, and dynamite, are moving at a high rate of speed down a roadway not too far from you.

Now, the good news: America's track record in transporting these materials is about as safe as they come. Very rarely, almost never in fact, are the potential dangers of these transports realized, largely due to instituted safeguards that seem to work very well.

However, accidents can happen. Take the August 2005 incident in Spanish Fork Canyon, Utah, for instance. A truck carrying 35,500 pounds of explosives—specifically small boosters used in seismic testing—overturned and exploded, creating a crater in the highway estimated to be between 20 to 35 feet deep and 70 feet wide according to the Utah Department of Transportation. But the damage wasn't solely financial. Four people, including the truck driver and a passenger, were hospitalized.

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.

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.

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.

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.

007Because 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.

clearview vishuman1 001
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.

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.

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.

marclab retinaDespite great advances in neuroscience and medical technology in recent decades, nearly ten million Americans still suffer blindness due to retinal degenerative diseases such as retinitis pigmentosa (RP), age-related macular degeneration (AMD), diabetic retinopathy, and glaucoma. Unfortunately, current treatments available for these conditions are still quite limited. A primary challenge to developing effective treatments is the need for a complete understanding of the highly complex and delicate systems that compose the retina and how those systems change in response to degenerative disorders.

Remodeling processes that occur in the neuronal pathways within the retina during the course of retinal deterioration are of particular importance to the development of treatments for these conditions. Researchers at the Robert E. Marc Laboratory at the Moran Eye Center are collaborating with the SCI Institute on a project supported by the NIH-NIBIB (grant number 5R01EB005832) to develop high-throughput techniques for reconstructing and visualizing the neural structures that compose the retina in order to meet these challenges.

Scientific Background

retina anatomy