Biomedical Commons^™

Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso

Theses and Dissertations--Electrical and Computer Engineering

The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …

Novel Machine Learning And Wearable Sensor Based Solutions For Smart Healthcare Monitoring, Rajdeep Kumar Nath

Theses and Dissertations--Electrical and Computer Engineering

The advent of IoT has enabled the design of connected and integrated smart health monitoring systems. These health monitoring systems can be utilized for monitoring the mental and physical wellbeing of a person. Stress, anxiety, and hypertension are the major elements responsible for the plethora of physical and mental illnesses. In this context, the older population demands special attention because of the several age-related complications that exacerbate the effects of stress, anxiety, and hypertension. Monitoring stress, anxiety, and blood pressure regularly can prevent long-term damage by initiating necessary intervention or clinical treatment beforehand. This will improve the quality of life …

Self-Image Multimedia Technologies For Feedforward Observational Learning, Nkiruka M. A. Uzuegbunam

Theses and Dissertations--Electrical and Computer Engineering

This dissertation investigates the development and use of self-images in augmented reality systems for learning and learning-based activities. This work focuses on self- modeling, a particular form of learning, actively employed in various settings for therapy or teaching. In particular, this work aims to develop novel multimedia systems to support the display and rendering of augmented self-images. It aims to use interactivity (via games) as a means of obtaining imagery for use in creating augmented self-images. Two multimedia systems are developed, discussed and analyzed. The proposed systems are validated in terms of their technical innovation and their clinical efficacy in …

Properties And Optimization Of Respiratory Navigator Gating For Spiral Cine Dense Cardiac Mri, Sean Michael Hamlet

Theses and Dissertations--Electrical and Computer Engineering

Cardiac magnetic resonance (MR) imaging can non-invasively assess heart function. Displacement encoding with stimulated echoes (DENSE) is an advanced cardiac MR imaging technique that measures tissue displacement and can be used to quantify cardiac mechanics (e.g. strain and torsion). When combined with clinical risk factors, cardiac mechanics have been shown to be better predictors of mortality than traditional measures of heart function.

End-expiratory breath-holds are typically used to minimize respiratory motion artifacts. Unfortunately, requiring subjects to breath-hold introduces limitations with the duration of image acquisition and quality of data acquired, especially in patients with limited ability to hold their breath. …

Reference Compensation For Localized Surface-Plasmon Resonance Sensors, Neha Nehru

Theses and Dissertations--Electrical and Computer Engineering

Noble metal nanoparticles supporting localized surface plasmon resonances (LSPR) have been extensively investigated for label free detection of various biological and chemical interactions. When compared to other optical sensing techniques, LSPR sensors offer label-free detection of biomolecular interactions in localized sensing volume solutions. However, these sensors also suffer from a major disadvantage – LSPR sensors remain highly susceptible to interference because they respond to both solution refractive index change and non-specific binding as well as specific binding of the target analyte. These interactions can severely compromise the measurement of the target analyte in a complex unknown media and hence limit …

Multi-Mode Self-Referencing Surface Plasmon Resonance Sensors, Jing Guo

Theses and Dissertations--Electrical and Computer Engineering

Surface-plasmon-resonance (SPR) sensors are widely used in biological, chemical, medical, and environmental sensing. This dissertation describes the design and development of dual-mode, self-referencing SPR sensors supporting two surface-plasmon modes (long- and short-range) which can differentiate surface binding interactions from bulk index changes at a single sensing location. Dual-mode SPR sensors have been optimized for surface limit of detection (LOD). In a wavelength interrogated optical setup, both surface plasmons are simultaneously excited at the same location and incident angle but at different wavelengths. To improve the sensor performance, a new approach to dual-mode SPR sensing is presented that offers improved differentiation …