Characterization of Photoacoustic Flow Cytometry Signals

<p>Photoacoustic flow cytometry has been utilized to clinically determine the presence of melanoma circulating tumor cells (CTCs). Further investigation was conducted into the morphology of detection signals and how they could be manipulated to allow for further classification. Novel features were extracted from waveforms that appear to have strong classification ability. Neural networks were also used to determine classification potential and the creation of feature mapping for future unsupervised classification. Detections were expanded from single waves to a time dependent multiwave event. Waveforms were also determined to be of non-parametric distribution, allowing for classification by neural network but not allowing for reduction into feature maps with techniques used in the study.</p>

Name thesis:degree_name

MS

Level thesis:degree_level

Immediate Access

Discipline thesis:degree_discipline

Biomedical Engineering

Year dc:date.available

2020

Author dc:creator

• Benzinger, Craig

Contributors dc:contributor

• John Viator
• Rana Zakerzadeh

• Photoacoustic
• Flow
• Cytometry
• Signals
• Characterization
• Biomedical Devices and Instrumentation
• Biomedical Engineering and Bioengineering

Language dc:language

English

Repository record dc:identifier

https://dsc.duq.edu/etd/1891

OAI identifier oai:identifier

oai:dsc.duq.edu:etd-2902