Sequential processing of quantitative phase images for the study of cell behaviour in real‐time digital holographic microscopy

• Published in: Journal of microscopy (Oxford) Vol. 256; no. 2; pp. 117 - 125
• Main Authors: ZIKMUND, T., KVASNICA, L., TÝČ, M., KŘÍŽOVÁ, A., ČOLLÁKOVÁ, J., CHMELÍK, R.
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 01.11.2014
• Subjects: Aberration compensation; Algorithms; Animals; Cell Line, Tumor; cell tracking; digital image processing; Fibrosarcoma - pathology; Holography - methods; Image Interpretation, Computer-Assisted - methods; Microscopy; Microscopy, Phase-Contrast - methods; quantitative phase imaging; Rats; real‐time holography; digital image processing; cell tracking; real-time holography; Aberration compensation; quantitative phase imaging
• ISSN: 0022-2720; 1365-2818
• DOI: 10.1111/jmi.12165

Summary Transmitted light holographic microscopy is particularly used for quantitative phase imaging of transparent microscopic objects such as living cells. The study of the cell is based on extraction of the dynamic data on cell behaviour from the time‐lapse sequence of the phase images. However, the phase images are affected by the phase aberrations that make the analysis particularly difficult. This is because the phase deformation is prone to change during long‐term experiments. Here, we present a novel algorithm for sequential processing of living cells phase images in a time‐lapse sequence. The algorithm compensates for the deformation of a phase image using weighted least‐squares surface fitting. Moreover, it identifies and segments the individual cells in the phase image. All these procedures are performed automatically and applied immediately after obtaining every single phase image. This property of the algorithm is important for real‐time cell quantitative phase imaging and instantaneous control of the course of the experiment by playback of the recorded sequence up to actual time. Such operator's intervention is a forerunner of process automation derived from image analysis. The efficiency of the propounded algorithm is demonstrated on images of rat fibrosarcoma cells using an off‐axis holographic microscope. Lay Description Digital holographic microscopy is a powerful technique which allows digital recording and numerical reconstruction of both light compounds — amplitude and phase. Transmitted‐light microscopy turned out as a suitable tool for observing living cells because of its noninvasive nature. The phase image can be quantitatively retrieved with high accuracy and in real time. The phase images are affected by outer influences (resulting in phase deformation) making exploitation the method's full potential of recording the observed sample particularly difficult. Moreover, the phase deformation changes during long‐term experiments. A lot of work has been done to compensate the deformation to date, but they always have severe disadvantages. We use a novel algorithm for processing of living cells phase images in a time‐lapse sequence. The algorithm compensates for the complete deformation of a phase image using a surface approximating the background of the image. The fuzzy logic is applied for calculation of the surface. Moreover, the algorithm identifies and segments an individual cell in the images. Most importantly, all these procedures are performed automatically and applied immediately after obtaining every single phase image. This property of the algorithm is essential for real‐time observation and experiment control.