Understanding the Morphology of Brain Disorders
Advances in medical imaging devices, such as magnetic resonance imaging (MRI), have led to our ability to acquire detailed information about the living human brain, including its anatomical structure, function, and connectivity. However, making sense of this complex data is a difficult task, especially in large imaging studies that may include hundreds or even thousands of participants. This is where computer science can play an important role. Image analysis algorithms can automatically quantify properties of the brain, such as the size of brain structures, or the functional activity in different brain regions. This provides neuroscience researchers with insights into how the brain functions and what abnormalities are present in diseased brains.
Neuro Stimulation
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| Transcranial Magnetic Stimulation (TMS) of the human motor cortex. |
SCIRun 5 Development
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.
Mesh Generation and Cleaver
 Figure 1: 3D surface mesh of a face. |
Evolution of the Medical Classroom
Introducing 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.
Big Data, Big Business
From the University of Utah: Feb. 7, 2014 – The University of Utah's College of Engineering received approval this week for its new graduate certificate program in big data.This emerging field – which addresses large sets of data too complex, diverse or rapidly changing for one computer to handle – affects everything from studying traffic patterns to managing sensitive information online. Big data is also big business – for example, using big data to improve efficiency and quality in the health care sector is estimated to be worth more than $300 billion each year.
"We're seeing a revolution in the availability of data. It's easy to collect information, but processing and analyzing large stores of data is becoming increasingly difficult. We are at the point where the traditional analytical tools for attacking this problem are breaking down," says Jeff Phillips, assistant professor of computer science and coordinator of the new program.
Computer Simulation of Blood Vessel Growth: Early Step toward Treatment for Diseases that Affect Blood Flow
Jan. 22, 2014 – University of Utah bioengineers showed that tiny blood vessels grow better in the laboratory if the tissue surrounding them is less dense. Then the researchers created a computer simulation to predict such growth accurately – an early step toward treatments to provide blood supply to tissues damaged by diabetes and heart attacks and to skin grafts and implanted ligaments and tendons.
Academic Senate approves new certificates
Press Release from The Utah Daily ChronicleBy Nathan Turner on October 7, 2013.
Contact Nathan Turner at
The October session of the Academic Senate approved a proposed cross-disciplinary certificate to the College of Engineering and Scientific Computing and Imaging Institute on Monday evening.
Fresh Tracks
Welcome to the Fresh Tracks Newsletter, highlighting news from the SCI Institute. Since our first newsletter six months ago, SCI Institute faculty, staff, and students have continued to perform exciting research, lead international conferences, perform important professional service, and educate students at the graduate, undergraduate, and even high school levels.
UDCC Open House
Wednesday, September 11th11 am to 2 pm
University of Utah
Warnock Engineering Building, Catmull Gallary
72 So. Central Campus Dr.
The first UDCC open house will bring together our consortium partners and engineering students to a single venue. Partners interested in sponsoring student internships through the new Data Center Engineering Certificate will be present for questions, and students will have the opportunity to hear from and engage with some of our nation's leading experts in the field. You can visit our website or email us for more information.