Category Archives: Research Resources

Original Research: A Framework for Image-Based Modeling of Acute Myocardial Ischemia Using Intramurally Recorded Extracellular Potentials

My co-authored research article titled – A Framework for Image-Based Modeling of Acute Myocardial Ischemia Using Intramurally Recorded Extracellular Potentials was published in the peer review journal – Annals of Biomedical Engineering. The article is available in print, in the September 2018 issue of the journal.

Briefly, the manuscript documents a simulation framework for incorporating subject-specific, geometric models and experimental results that are highly resolved in space and time into computational models. This framework provides a means to advance the understanding of the underlying mechanisms of ischemic disease while simultaneously putting in place the computational infrastructure necessary to study and improve ischemia models aimed at reducing diagnostic errors in the clinic. The article can be accessed here

Research Paper published

My research paper titled – Sensitivity of epicardial electrical markers to acute ischemia detection was accepted for publishing in the peer-reviewed journal – Journal of Electrocardiology. The article will be available in print, in the December 2014 issue of the journal.

Briefly, the research focuses on the electrical behavior of the heart during ischemic conditions, which is a precursor to myocardial infarction (heart attack). Specifically, the study evaluated different electrical markers and their ability to detect early onset of acute myocardial ischemia. The  paper reported the findings from the study and can be accessed here.

Small Animal Imaging Facility

SAIF_s

Small Animal Imaging Facility (SAIF) is also affiliated with University of Utah.  All of our anatomical scans of the heart, the micro-vasculature and cardiac fibers are acquired using their state of the art MRI (7 Tesla) and CT scanners.  More information about SAIF can be found here.

Scientific Computing & Imaging (SCI)

SCI_s

Scientific Computing  & Imaging (SCI) Institute is also affiliated with the University of Utah and is renowned for cutting edge research in scientific computing and visualization. We use several of their image processing and scientific visualization tools for our bio-signal visualization and analysis.  More information about SCI can be found here