|M.Sc Student||Alterman Marina|
|Subject||Theory of Multiplexed Fluorescence Unmixing|
|Department||Department of Electrical Engineering||Supervisor||Professor Yoav Schechner|
|Full Thesis text|
Multiplexed imaging and illumination have been used to recover enhanced arrays of intensity or spectral reflectance samples, per pixel.
However, these arrays themselves are often not the ultimate goal of a system. Rather, the intensity or reflectance is a result of underlying object characteristics. For example, spectral reflectance, emission or absorption distributions stem from an underlying mixture of materials. Systems thus try to infer concentrations of these underlying mixed components: computational analysis does not end with recovery of intensity (or equivalent) arrays.
The process of inverting mixtures is termed unmixing. It is central in many problems. We incorporate the mixing/unmixing process explicitly into the optimization of multiplexing codes. This way, optimal recovery of underlying components (materials) is achieved. In the absence of this integrated optimization, multiplexed imaging can even harm the quality of unmixing. Moreover, by directly defining the goal of data acquisition to be recovery of components (materials) instead of intensity/reflectance arrays, the acquisition becomes more efficient. We apply this approach to fluorescence imaging, where the elaborate image formation model and characteristics are incorporated. This yields significant generalizations of multiplexing theory.