Biomedical Engineering and Bioengineering Commons^™

Improving The Performance And Evaluation Of Computer-Assisted Semen Analysis, Ji-Won Choi

Dissertations

Semen analysis is performed routinely in fertility clinics to analyze the quality of semen and sperm cells of male patients. The analysis is typically performed by trained technicians or by Computer-Assisted Semen Analysis (CASA) systems. Manual semen analysis performed by technicians is subjective, time-consuming, and laborious, and yet most fertility clinics perform semen analysis in this manner. CASA systems, which are designed to perform the same tasks automatically, have a considerable market share, yet many studies still express concerns about their accuracy and consistency. In this dissertation, the focus is on detection, tracking, and classification of sperm cells in semen …

Skin Tone Tracking Device (Chromaband), Ziyang Bian

Computer Engineering

It’s long been said that your skin is a window into your health and with many illnesses the first signs of trouble actually show up in your skin. So if we have this natural warning system, then why isn’t anyone able to effectively use it to predict changes in our health? The problem is that currently there is no reliable way to accurately measure the change in skin tone and how these changes may or may not change with variations in health. This project’s aim is to design and develop a device that will record the changes in a user’s …

Detecting, Segmenting And Tracking Bio-Medical Objects, Mingzhong Li

Doctoral Dissertations

"Studying the behavior patterns of biomedical objects helps scientists understand the underlying mechanisms. With computer vision techniques, automated monitoring can be implemented for efficient and effective analysis in biomedical studies. Promising applications have been carried out in various research topics, including insect group monitoring, malignant cell detection and segmentation, human organ segmentation and nano-particle tracking.

In general, applications of computer vision techniques in monitoring biomedical objects include the following stages: detection, segmentation and tracking. Challenges in each stage will potentially lead to unsatisfactory results of automated monitoring. These challenges include different foreground-background contrast, fast motion blur, clutter, object overlap and …