Monte Carlo Simulations for Analyzing Optical Microscopy
Friday, 19 August 2011: 13.45-14.30
Amir Gandjbakhche, National Institutes of Health
Optical imaging of tissue of all forms is limited at some point by the relationship between resolution and depth of penetration. Approaches, such as adaptive optics, are continually being proposed in hardware to push back this limit. However we are now reaching the point where novel approaches are running out and we are reaching close to a fundamental hard limit of imaging. New approaches to handle this are expensive and can be difficult to implement, further the expected gain is not always obtained/obtainable. It is even true that in some cases (e.g. adaptive optics) mathematical implementations in software may be possible to obtain similar results to those generated using more expensive hardware techniques. The question that arises is how do we decide which avenues to pursue?
In this work we propose that numerical modeling of the imaging modalities, whilst previously prohibitively computationally expensive, is becoming (a) more tractable on standard architectures and (b) we are continuously raising the cost-effectiveness margin. To illustrate this point, we will present two studies one where we have been able to quantify a novel imaging technique [total emission detection(TED) in 2-photon imaging] and to aid in its further development and another where we are studying an existing technique to examine absolute limitations in an effort to determine the viability of future enhancements [studying the effects of scatter in fluorescence correlation spectroscopy]. In the former case we will also touch upon a very important question, in adaptive optics the assumption is that large scale refractive index boundaries are the primary depth limiting effect in con-focal imaging, however we show that for TED the limiting effect was the background scatter. This raises the idea that using modeling and simulation to guide our research may be becoming much more of a significant issue than previously considered.
We hypothesize that the idea of using “virtual optical imaging” to facilitate, quantify and guide the future of Biophotonics will be the most beneficial approach available.