Low-intensity illumination for lensless digital holographic microscopy with minimized sample interaction.
Bartosz MireckiMikołaj RogalskiPiotr ArcabPiotr RogujskiLuiza StanaszekMichał JózwikMaciej TrusiakPublished in: Biomedical optics express (2022)
Exposure to laser light alters cell culture examination via optical microscopic imaging techniques based on label-free coherent digital holography. To mitigate this detrimental feature, researchers tend to use a broader spectrum and lower intensity of illumination, which can decrease the quality of holographic imaging due to lower resolution and higher noise. We study the lensless digital holographic microscopy (LDHM) ability to operate in the low photon budget (LPB) regime to enable imaging of unimpaired live cells with minimized sample interaction. Low-cost off-the-shelf components are used, promoting the usability of such a straightforward approach. We show that recording data in the LPB regime (down to 7 µW of illumination power) does not limit the contrast or resolution of the hologram phase and amplitude reconstruction compared to regular illumination. The LPB generates hardware camera shot noise, however, to be effectively minimized via numerical denoising. The ability to obtain high-quality, high-resolution optical complex field reconstruction was confirmed using the USAF 1951 amplitude sample, phase resolution test target, and finally, live glial restricted progenitor cells (as a challenging strongly absorbing and scattering biomedical sample). The proposed approach based on severely limiting the photon budget in lensless holographic microscopy method can open new avenues in high-throughout (optimal resolution, large field-of-view, and high signal-to-noise-ratio single-hologram reconstruction) cell culture imaging with minimized sample interaction.
Keyphrases
- high resolution
- high speed
- single molecule
- label free
- mass spectrometry
- low cost
- air pollution
- machine learning
- induced apoptosis
- magnetic resonance
- tandem mass spectrometry
- big data
- electronic health record
- computed tomography
- oxidative stress
- convolutional neural network
- cell death
- cell cycle arrest
- social media
- deep learning
- cell proliferation
- spinal cord