Engineering Commons^™

Spatial Frequency Domain Imaging Of Short-Wave Infrared Fluorescence For Biomedical Applications, Joseph P. Leonor

ENGS 88 Honors Thesis (AB Students)

Fluorescence imaging has become a standard in many clinical applications, such as tumor and vasculature imaging. One application that is becoming more prominent in cancer treatment is fluorescence-guided surgery (FGS). Currently, FGS allows surgeons the ability to visually navigate tumors and tissue structures intraoperatively. As a result, they can remove tumor more efficiently while maintaining critical structures within the patient, creating better outcomes and lower recovery times. However, background fluorescence and inability to localize depth create challenges when determining resection boundaries.

Different techniques, such as spatially modulating the illumination and imaging at longer light wavelengths, have been developed to accurately …

Abso2luteu-Net: Tissue Oxygenation Calculation Using Photoacoustic Imaging And Convolutional Neural Networks, Kevin Hoffer-Hawlik, Geoffrey P. Luke

ENGS 88 Honors Thesis (AB Students)

Photoacoustic (PA) imaging uses incident light to generate ultrasound signals within tissues. Using PA imaging to accurately measure hemoglobin concentration and calculate oxygenation (sO₂) requires prior tissue knowledge and costly computational methods. However, this thesis shows that machine learning algorithms can accurately and quickly estimate sO₂. absO₂luteU-Net, a convolutional neural network, was trained on Monte Carlo simulated multispectral PA data and predicted sO₂ with higher accuracy compared to simple linear unmixing, suggesting machine learning can solve the fluence estimation problem. This project was funded by the Kaminsky Family Fund and the Neukom Institute.