Cell-sensitive phase contrast microscopy imaging by multiple exposures

• The proposed cell-sensitive imaging by taking multiple exposures of phase contrast microscopy images on the same petri dish estimates a camera response function which responds to cells but generates a constant response to non-cell background.
• The cell-sensitive microscopy imaging is a novel way of imaging live cells in a petri dish. The result of this new imaging method is visually superior quality, which reveals the appearance details of cells under multiple exposures and suppresses background noise near zero.
• The cell-sensitive imaging inverses the optical processing chain to restore the irradiance signal right after the phase contrast microscope, thus removing the nonlinear function mapping introduced by camera sensors and uncovering the cells’ true physical properties.
• In the restored irradiance signal map, non-cell background region has a constant irradiance different from those of cells, which will greatly facilitate the cell segmentation task since simple thresholding techniques can be applied to classify cell signals from background signals.

We propose a novel way of imaging live cells in a Petri dish by the phase contrast microscope. By taking multiple exposures of phase contrast microscopy images on the same cell dish, we estimate a cell-sensitive camera response function which responds to cells’ irradiance signals but generates a constant on non-cell background signal. The result of this new microscopy imaging is visually superior quality, which reveals the appearance details of cells and suppresses background noise near zero. Using the cell-sensitive microscopy imaging, cells’ original irradiance signals are restored from all exposures and the irradiance signals on non-cell background regions are restored as a uniform constant (i.e., the imaging system is sensitive to cells only but insensitive to non-cell background). The restored irradiance signals greatly facilitate the cell segmentation by simple thresholding. The experimental results validate that high quality cell segmentation can be achieved by our approach.

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