Quantitative Phase Imaging

Quantitative Phase Imaging: Multi-Modal Imaging Approaches

Quantitative Phase Imaging (QPI) has emerged as a powerful and non-invasive technique for investigating the optical properties of transparent and semi-transparent specimens. Unlike traditional microscopy methods that rely on staining or labeling samples, QPI provides valuable insights into the structural and biochemical composition of cells and tissues without altering their natural state. This article by Academic Block delves into the principles, techniques, and applications of Quantitative Phase Imaging, showcasing its significance in various scientific and medical domains.

Understanding the Basics

Quantitative Phase Imaging is grounded in the principles of interferometry and phase contrast microscopy. The technique captures the phase shift of light as it passes through a transparent specimen, allowing researchers to visualize minute changes in refractive index. Refractive index variations are directly related to the specimen’s thickness, density, and composition. By quantifying these optical changes, QPI enables the creation of high-resolution, label-free images.

Principles of Quantitative Phase Imaging

  1. Interferometry: QPI employs interferometry to measure the phase shift induced by the specimen. Interferometers split a light beam into two paths, one interacting with the specimen and the other acting as a reference. The interference pattern reveals the phase shift caused by the specimen, providing detailed information about its structure.

  2. Phase Retrieval Algorithms: Sophisticated algorithms are used to extract quantitative information from the interferograms. These algorithms convert phase information into quantitative maps of specimen parameters, such as thickness and refractive index.

Techniques in Quantitative Phase Imaging

Several techniques fall under the umbrella of Quantitative Phase Imaging, each with its unique advantages:

  1. Digital Holographic Microscopy (DHM): DHM records both intensity and phase information by capturing holograms of specimens. This technique enables three-dimensional imaging and is particularly useful for live-cell imaging.

  2. Spatial Light Interference Microscopy (SLIM): SLIM combines phase-shifting interferometry with white-light microscopy, providing high-speed imaging capabilities. It is well-suited for dynamic processes, such as cell migration and division.

  3. Quantitative Phase Imaging using Fourier Transform (QPI-FT): This technique utilizes Fourier transform methods to extract phase information, offering high sensitivity and accuracy in measuring refractive index changes.

Applications of Quantitative Phase Imaging

  1. Biological and Medical Imaging: QPI has found widespread applications in the study of living cells, tissues, and biomaterials. Its label-free nature makes it invaluable for observing dynamic cellular processes, such as cell division and migration, without affecting cell viability.

  2. Material Science: In material science, QPI is used to investigate the structural properties of materials, such as thin films and nanoparticles. This is crucial for developing advanced materials with specific optical characteristics.

  3. Microfluidics: QPI plays a vital role in microfluidic research by providing real-time monitoring of fluid dynamics and interactions at the microscale.

  4. Clinical Diagnostics: QPI has potential applications in clinical settings, offering a non-invasive tool for diagnosing diseases and monitoring cellular changes associated with various medical conditions.

Mathematical equations behind the Quantitative Phase Imaging

Quantitative Phase Imaging (QPI) involves the use of mathematical equations and algorithms to extract quantitative information from phase measurements. The specific equations may vary depending on the technique employed, but here are some fundamental principles and equations associated with QPI:

  1. Phase Shift Measurement:

    The basic concept in QPI is to measure the phase shift introduced by a transparent specimen. The phase shift (Δϕ) is related to the optical path length difference (OPD) between the sample and reference arms of the interferometer:

    Δϕ = 2π⋅( OPD / λ ) ;


    • Δϕ is the phase shift,
    • OPD is the optical path length difference,
    • λ is the wavelength of the light source.
  2. Refractive Index Reconstruction:

    The refractive index (n) of the specimen can be related to the phase shift by the following equation:

    n = 1 + (Δϕ / 2πk) ;


    • n is the refractive index,
    • Δϕ is the phase shift,
    • k is the wavenumber (k = 2π / λ).
  3. Phase Unwrapping:

    In digital holography or interferometry, the obtained phase information may be wrapped, meaning it is limited to a certain range (usually between and π). Phase unwrapping algorithms are employed to extend the phase values beyond this range:

    Unwrapped_Phase = atan2(sin⁡(Wrapped_Phase), cos⁡(Wrapped_Phase)) ;

    This equation ensures that the unwrapped phase maintains continuity and provides a complete map of the phase distribution.

  4. Fourier Transform Method:

    In some QPI techniques, such as Quantitative Phase Imaging using Fourier Transform (QPI-FT), the phase information is obtained through Fourier analysis of the recorded interference pattern. The phase shift map (Δϕ) can be calculated from the Fourier-transformed hologram as:

    Δϕ = arg(Fourier(Hologram)) ;

    This equation extracts the phase information from the spatial frequencies in the Fourier domain.

  5. Propagation of Light through a Sample:

    In certain QPI methods, especially those dealing with thick samples, the propagation of light through the specimen can be modeled using the angular spectrum propagation method:

    U(z) = FFT−1{FFT{U0(x,y)}⋅exp⁡[ik sqrt (k2 − (ω2 / c2) ) z ] } ;


    • U(z) is the complex field at a distance z from the specimen,
    • U0(x,y) is the complex field at the specimen plane,
    • k is the wavenumber,
    • ω is the radial frequency,
    • c is the speed of light.

These equations represent just a few examples, and the specific mathematical formulations can vary depending on the QPI technique and the underlying principles of the imaging method used.

Challenges and Future Directions

Despite its numerous advantages, Quantitative Phase Imaging is not without challenges. Issues such as sensitivity to environmental conditions and limitations in imaging speed are areas of ongoing research. Future developments may focus on improving the robustness and versatility of QPI techniques, potentially expanding its applications in fields like neuroscience and drug discovery.

Final Words

In this article by Academic Block we have seen that, Quantitative Phase Imaging stands at the forefront of modern microscopy, providing a wealth of information without the need for exogenous labels. Its applications in biological research, materials science, and clinical diagnostics showcase its versatility and potential impact on various scientific disciplines. As technology continues to advance, Quantitative Phase Imaging is poised to unravel the mysteries of the microscopic world, opening new frontiers in scientific discovery and medical diagnostics. Please provide your comments below, it will help us in improving this article. Thanks for reading!

List Discoveries Where is Quantitative Phase Imaging is used

  1. Cell Biology and Life Sciences:

    • Cell Morphology and Dynamics: QPI has been extensively used to study cellular morphology, providing insights into cell shape, volume, and dynamics without the need for staining or labeling. This has contributed to a better understanding of cellular processes such as mitosis, migration, and apoptosis.

    • Label-Free Live-Cell Imaging: QPI techniques, including Digital Holographic Microscopy (DHM) and Spatial Light Interference Microscopy (SLIM), enable label-free imaging of live cells. This has been crucial for observing dynamic cellular processes in real-time, allowing researchers to study cell behavior without introducing exogenous agents.

  2. Neuroscience:

    • Neuronal Imaging: QPI has been applied to study neurons and neural networks, providing non-invasive and label-free imaging of neuronal morphology and activity. This has implications for understanding brain function, neurodegenerative diseases, and drug screening.

  3. Biomedical Diagnostics:

    • Clinical Pathology and Disease Diagnosis: QPI has been explored for clinical applications, including the diagnosis of diseases such as cancer. The technique’s ability to provide detailed information about cellular structure and density makes it valuable for detecting abnormalities in tissues.

    • Red Blood Cell Analysis: QPI has been used to study the mechanical properties of red blood cells, contributing to the understanding of diseases related to blood disorders and improving diagnostic capabilities.

  4. Microfluidics and Biotechnology:

    • Microfluidic Studies: QPI has been employed to investigate fluid dynamics and interactions at the microscale in microfluidic devices. This is valuable for applications in drug delivery, lab-on-a-chip technologies, and understanding cellular responses in confined environments.

    • Label-Free Analysis of Biomolecules: QPI has been used to study biomolecular interactions and conformational changes without the need for fluorescent labels. This has implications for drug discovery and the development of biosensors.

  5. Materials Science:

    • Material Characterization: QPI techniques have been applied to study the optical properties of materials, including thin films and nanoparticles. This is crucial for the development of advanced materials with specific optical characteristics.

    • Surface Profilometry: QPI can be used for high-resolution surface profiling, providing insights into the topography of materials at the nanoscale.

  6. Quantitative Imaging in Microscopy:

    • 3D Imaging: QPI enables three-dimensional imaging without the need for physical sectioning or staining. This has been instrumental in understanding the spatial organization of cellular structures.

    • High-Resolution Imaging: QPI techniques have contributed to achieving high-resolution imaging beyond the diffraction limit, providing detailed information at the nanoscale.

Quantitative Phase Imaging

Hardware and software required for Quantitative Phase Imaging

Hardware Requirements:
  1. Light Source: A stable and coherent light source is essential for interference-based QPI techniques. Common sources include lasers or white light with appropriate filters.

  2. Interferometer: An interferometer is a key component in many QPI setups. It splits light into reference and sample beams, allowing the measurement of phase differences.

  3. Microscope Setup: A microscope is often used to focus the light on the specimen and collect the transmitted or reflected light.

  4. Optical Components: Various lenses, mirrors, and beam splitters are required to manipulate and direct the light through the optical system.

  5. Camera: A high-resolution camera is used to capture the interference pattern or hologram created by the interaction of the sample and reference beams.

  6. Stage and Objective Lens: A precise stage allows for the accurate positioning of the sample, and a high-quality objective lens is crucial for obtaining detailed images.

  7. Detector: Detectors, such as CCD or CMOS cameras, are used to record the intensity or interference pattern at the image plane.

  8. Computing System: A computer is needed to control the hardware components, acquire and store images, and run the necessary data analysis software.

Software Requirements:
  1. Data Acquisition Software: Software is required to control the camera, stage, and other hardware components during image acquisition.

  2. Image Processing Software: Image processing software is used to preprocess raw images, correct for aberrations, and enhance the quality of acquired data.

  3. Phase Retrieval Algorithms: Specialized algorithms are employed to retrieve the quantitative phase information from the captured interference patterns or holograms. Common methods include Fourier transform, phase unwrapping, and iterative algorithms.

  4. Numerical Analysis Tools: Software tools for numerical analysis are often used to extract quantitative parameters from the phase information, such as refractive index or sample thickness.

  5. Visualization Software: Tools for visualizing and interpreting the reconstructed phase images are crucial for researchers to understand and analyze the acquired data.

  6. 3D Reconstruction Software: For techniques that capture three-dimensional information, software capable of reconstructing 3D images from stacks of 2D images is necessary.

  7. Data Storage and Management: Efficient data storage and management tools are essential, especially for large datasets generated during 3D imaging or time-lapse experiments.

  8. Graphical User Interface (GUI): User-friendly interfaces facilitate the control of the hardware and software components, making the system accessible to researchers.

Facts on Quantitative Phase Imaging

Label-Free Imaging: Quantitative Phase Imaging (QPI) is a label-free imaging technique, meaning it does not require the use of exogenous dyes or stains to visualize specimens. This is advantageous for studying live cells and tissues in their natural state.

Refractive Index Sensitivity: QPI is highly sensitive to changes in refractive index. The technique exploits the fact that light undergoes a phase shift as it passes through regions with different refractive indices, allowing for the quantitative mapping of optical path length variations.

Real-Time Monitoring: Certain QPI methods, such as Spatial Light Interference Microscopy (SLIM) and Digital Holographic Microscopy (DHM), enable real-time monitoring of dynamic biological processes. This is crucial for studying live cell behavior, cell division, and other time-sensitive phenomena.

Applications in Clinical Diagnosis: QPI has shown promise in clinical settings for diagnostic purposes. It has been applied to study pathological changes in tissues, aiding in the diagnosis of diseases such as cancer. The label-free nature of QPI is particularly beneficial in clinical applications.

Material Science and Nanotechnology: In addition to biological applications, QPI is extensively used in material science to characterize the optical properties of materials at the micro and nanoscale. This is valuable for the development of advanced materials and nanotechnologies.

3D Imaging Capability: QPI techniques often offer three-dimensional imaging capabilities. This allows researchers to reconstruct the spatial organization of structures within specimens, providing a more comprehensive understanding of their morphology.

High-Resolution Beyond the Diffraction Limit: QPI has the potential to achieve high-resolution imaging beyond the diffraction limit of light. This is crucial for visualizing fine details at the nanoscale, contributing to advancements in microscopy.

Quantitative Data Extraction: The primary strength of QPI lies in its ability to provide quantitative information about the studied specimens. Parameters such as refractive index, thickness, and volume can be extracted and analyzed, facilitating a deeper understanding of biological and materials-related processes.

Interferometric Principles: QPI is rooted in interferometric principles, where interference patterns created by the interaction of light waves are analyzed to extract phase information. This reliance on interferometry allows for precise measurements of optical phase shifts.

Multimodal Imaging Integration: QPI is often integrated with other imaging modalities, such as fluorescence microscopy or Raman spectroscopy, to provide complementary information. This multimodal approach enhances the overall understanding of biological samples.

Non-Invasive Nature: QPI is a non-invasive imaging technique, which means it does not perturb the biological or material samples being studied. This is crucial for maintaining the natural state of specimens and avoiding potential artifacts introduced by labeling or staining.

Academic References on Quantitative Phase Imaging


  1. Smith, J. D. (2010). Quantitative Phase Imaging: Principles and Applications. Academic Press.

  2. Johnson, R. S. (2015). Introduction to Digital Holography. Springer.

  3. Brown, M. A., & Wilson, P. L. (2018). Advanced Techniques in Quantitative Microscopy. Wiley.

  4. Garcia, R., & Kreuzer, H. J. (Eds.). (2012). Interferometric and Synchrotron Techniques in Nanoscience. Springer.

  5. Marquet, P., & Rappaz, B. (2005). Digital Holographic Microscopy: A Noninvasive Contrast Imaging Technique allowing Quantitative Visualization of Living Cells with Subwavelength Axial Accuracy. Optics Letters, 30(5), 468-470.

Journal Articles:

  1. Popescu, G., et al. (2007). Optical imaging of cell mass and growth dynamics. American Journal of Physiology-Cell Physiology, 294(4), C817-C822.

  2. Xu, W., & Jericho, M. H. (2001). Digital in-line holography for biological applications. Proceedings of the National Academy of Sciences, 98(20), 11301-11305.

  3. Marquet, P., et al. (2005). Digital Holographic Microscopy: a Noninvasive Contrast Imaging Technique allowing Quantitative Visualization of Living Cells with Subwavelength Axial Accuracy. Optics Letters, 30(5), 468-470.

  4. Kemper, B., et al. (2007). Integral refractive index determination of living suspension cells by multifocus digital holographic phase contrast microscopy. Journal of Microscopy, 226(1), 1-9.

  5. Xu, W., & Kreuzer, H. J. (2001). Digital In-Line Holography for Biological Applications. Proceedings of the National Academy of Sciences, 98(20), 11301-11305.

  6. Mann, C. J., et al. (2016). Quantitative phase imaging for cell culture quality control. Biotechnology Journal, 11(12), 1570-1578.

  7. Marquet, P., et al. (2005). Digital Holographic Microscopy: A Noninvasive Contrast Imaging Technique allowing Quantitative Visualization of Living Cells with Subwavelength Axial Accuracy. Optics Letters, 30(5), 468-470.

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