Erythrocyte morphology is an important factor in disease diagnosis, however, traditional setups as microscopes and cytometers cannot provide enough quantitative information of cellular morphology for in-depth statistics and analysis. In order to capture variations of erythrocytes affected by metal ions, quantitative interferometric microscopy (QIM) is applied to monitor their morphology changes. Combined with phase retrieval and cell recognition, erythrocyte phase images, as well as phase area and volume, can be accurately and automatically obtained. The research proves that QIM is an effective tool in cellular observation and measurement.
Quantitative interferometric microscopy is an important method for observing biological samples such as cells and tissues. In order to obtain continuous phase distribution of the sample from the interferogram, phase extracting and phase unwrapping are both needed in quantitative interferometric microscopy. Phase extracting includes fast Fourier transform method and Hilbert transform method, etc., almost all of them are rapid methods. However, traditional unwrapping methods such as least squares algorithm, minimum network flow method, etc. are time-consuming to locate the phase discontinuities which lead to low processing efficiency. Other proposed high-speed phase unwrapping methods always need at least two interferograms to recover final phase distributions which cannot realize real time processing. Therefore, high-speed phase unwrapping algorithm for single interferogram is required to improve the calculation efficiency. Here, we propose a fast phase unwrapping algorithm to realize high-speed quantitative interferometric microscopy, by shifting mod 2π wrapped phase map for one pixel, then multiplying the original phase map and the shifted one, then the phase discontinuities location can be easily determined. Both numerical simulation and experiments confirm that the algorithm features fast, precise and reliable.