Abstract: The focus of this thesis is to develop novel label-free optical imaging techniques to study mitochondrial heterogeneity in cultured human fibroblasts. Mitochondrial heterogeneity is a condition that occurs when a cell or tissue contains both healthy and diseased mitochondrial DNA. The quantification of healthy and diseased mitochondria is a crucial factor in identifying mitochondrial disease. We hypothesize that transient absorption microscopy, which utilizes femtosecond laser pulses to measure sub pico-second excited state relaxation mechanisms of electron transport chain (ETC) hemeproteins, can quantify intracellular mitochondrial heterogeneity. As proof-of-concept, we report our findings on collecting live human cultured fibroblast images using transient absorption microscopy technique. We also detail the technical challenges faced and overcome primarily related to low signal-to-noise (SNR) during pump-probe microscopy of live cells. Another aspect of this thesis is to develop unsupervised machine learning based algorithms to deal with the interpretability of transient absorption data. Time resolved microscopy techniques like fluorescence lifetime or transient absorption can have low signal-to-noise ratio or non-orthogonal exponentially decaying spectral signatures. We demonstrate how a simple convolutional neural network (CNN) based Autoencoder network can extract distinct molecular spectral signatures from transient absorption microscopy data. We also report on the possibility of using generative adversarial networks (GANs) to translate linear optical microscopy images of biological tissue to non-linear optical microscopy modality.

Adviser: Jesse Wilson
Co-Adviser: N/A
Non-ECE Member: Stuart Tobet, Biomedical Engineering
Member 3: Kevin Lear, Electrical and Computer Engineering
Addional Members: Randy Bartels

Publications:
1. A. C. Mugdha, A. J. Chicco, M. W. Friedrich, J. Van-Hove and J. W. Wilson, "Transient Absorption Microscopy of Fibroblasts", Frontiers in Optics and Laser Science Conference, Denver, CO, 2024

2. A.C. Mugdha and J.W. Wilson, "Blind hyperspectral unmixing of pump-probe images with maximum likelihood selection of a convolutional network from an ensemble of models", SPIE Photonics West Conference, San Francisco, CA, 2023

3. J.W. Wilson, E. Wang, A.C. Mugdha, L. Whitcomb and A. Chicco, "Label-free visible wavelength transient absorption imaging: mitochondrial redox contrast and unsupervised spectral learning", SPIE Optical Engineering + Applications Conference, San Diego, CA, 2022

4. E.E. Flater, A.C. Mugdha, S. Gupta, W.A. Hudson, A.A. Fahrenkamp, J.P. Killgore, J.W. Wilson, "Error estimation and enhanced stiffness sensitivity in contact resonance force microscopy with a multiple arbitrary frequency lock-in amplifier (MAFLIA)", Measurement Science and Technology, 2020

5. J.E. Nejad, A.C. Mugdha, J.W. Wilson, A.K. McGrew, and K.L. Lear, "Multifrequency Microfluidic Impedance Cytometer Using a Field-Programmable Gate Array for Parasite Egg Analysis", Proceedings of the Rocky Mountain Bioengineering Symposium (also published in the Biomedical Sciences Instrumentation journal), vol. 56, pp. 184-191, April 2020

6. A.C. Mugdha, J.W. Wilson, "Inferring nonlinear optical contrast from linear reflectance texture", SPIE Optical Engineering + Applications Conference, San Diego, CA, 2019

7. A.C. Mugdha and J.W. Wilson, "Machine learning approach to synthesizing multiphoton microscopic images from reflectance confocal", SPIE Photonics West Conference, San Francisco, CA, 2019

8. S. Gupta, A.C. Mugdha, W. Hudson, V. Palmer, K.L. Lear, J.W. Wilson, "Real-Time Time-Resolved Optical Measurements using a Digital Adaptive Filter", IEEE Photonics Conference (IPC), Reston, VA, 2018

Program of Study:
ECE-604
ECE-503
ECE-504
ECE-512
ECE-457
ECE-571
CS-545
CS-510