Biomedical Engineering and Bioengineering Commons^™

Characterizing Intervertebral Disc Strain Under Dynamic Loading Conditions Using Ultrasound Texture Analysis, Radhika Kulkarni

Discovery Undergraduate Interdisciplinary Research Internship

Herniated discs in the spine are a significant patient burden, with potential links to lower back and leg discomfort and a considerable impact on daily life. These discs, located between spinal vertebrae, are comprised of the annulus fibrosus (AF) and the nucleus pulposus (NP). Herniations happen when the NP protrudes through a full-thickness annular tear, possibly compressing spinal nerves. The mechanical factors underlying herniated discs are poorly understood, necessitating research into these mechanisms and accessible diagnostic techniques. Our study employs high-resolution ultrasound and texture correlation to quantify strain patterns in intervertebral discs during dynamic loading.

A motion segment from the …

Scanning Electron Microscopy Analysis Of Murine Renal, Aortic, And Cardiac Tissue, Sarah E. Grev, Luke E. Schepers, Jennifer Anderson, Craig J. Goergen

Discovery Undergraduate Interdisciplinary Research Internship

Scanning electron microscopy (SEM) is a tool that provides detailed insight into objects invisible to the human eye. As the name suggests, an electron beam is used to create an image down to the nanometer scale. The beam focuses on the surface of a sample using lenses in the electron column. In this project, we use SEM to study three types of murine tissue. First, we examine the glomerulus, found in the kidney, that is primarily responsible for filtering blood. Following a left renal vein (LRV) stenosis, SEM is used to observe changes to the glomeruli. Differences in the left …

Deep Learning Approach To Improved Image Quality For Medical Diagnostics, Olivia Loesch, Katie Leyba, Halyley Chan, Craig Goergen

Discovery Undergraduate Interdisciplinary Research Internship

The United Nation’s health-related Sustainable Development Goals are difficult to achieve in low- and middle-income countries due to workforce shortages and inadequate health surveillance systems. However, with the growth of artificial intelligence (AI) and computer algorithms, it is possible to apply AI to healthcare technologies to improve progress towards these UN standards. This project aims at using and improving computer algorithms and deep learning to aid in the extraction of important structural and functional information from murine carotid artery ultrasound and photoacoustic images. First, we created a large database of simulated photoacoustic images to optimize the algorithms. These images were …