Application of an Alternating Minimization Algorithm to Experimental DIC Microscopy Data for the Quantitative Determination of Sample Optical Properties
Differential Interference Contrast (DIC) is commonly chosen for imaging unstained transparent samples. One limitation of DIC microscopy is the qualitative results it provides. This must be post-processed to extract meaningful information. The Alternating Minimizatio (AM) algorithm studied in this thesis is an iterative approach to recover a quantitative estimate of a sample\u27s complex-valued transmittance function. The AM algorithm is validated using simulated data. Additionally, the bias retardation and shear distance, two characteristic features of the DIC system, must be measured to insure the system model is accurate. This is accomplished by introducing a calibrated liquid crystal device to the system. Algorithm performance is verified using an experimental test object before finally being applied to biological samples. Overall results demonstrate the accuracy of this algorithm\u27s object estimation results. These are verified through comparison to similar data processing techniques
