As light waves propagate through a medium, they experience a temporal delay, revealing vital information about the structural and compositional characteristics of the material. Quantitative Phase Imaging (QPI) is an advanced optical technique that captures variations in optical path length as light passes through biological samples, materials, and other transparent structures. Unlike traditional imaging methods that rely on staining or labeling, QPI allows researchers to visualize and quantify phase variations, generating high-contrast images for noninvasive investigations essential in fields such as biology, materials science, and engineering.
In a groundbreaking study published on July 25 in Advanced Photonics, researchers at the University of California, Los Angeles (UCLA) have introduced an innovative approach to 3D QPI using a wavelength-multiplexed diffractive optical processor. This new method addresses the limitations of traditional 3D QPI techniques, which are often time-consuming and computationally demanding.
The UCLA research team developed a wavelength-multiplexed diffractive optical processor that offers a novel solution for quantitative phase imaging of 3D phase-only objects. This processor uses multiple spatially engineered diffractive layers, optimized through deep learning, to optically transform the phase distributions of several 2D objects at different axial positions into intensity patterns. Each pattern is encoded in a unique wavelength channel and projected onto a single field-of-view (FOV) at the output plane of the diffractive processor. This innovative design allows for the capture of quantitative phase distributions of objects located at various axial planes using an intensity-only image sensor, eliminating the need for digital phase recovery algorithms.
“We are excited about the potential of this new approach for biomedical imaging and sensing,” said Aydogan Ozcan, lead researcher and Chancellor’s Professor at UCLA. “Our wavelength-multiplexed diffractive optical processor offers a novel solution for high-resolution, label-free imaging of transparent specimens, which could greatly benefit biomedical microscopy, sensing, and diagnostics applications.”
The innovative multiplane QPI system incorporates wavelength multiplexing and passive diffractive optical elements, collectively optimized through deep learning. By performing phase-to-intensity transformations that are spectrally multiplexed, this design enables rapid quantitative phase imaging of specimens across multiple axial planes. The system’s compactness and all-optical phase recovery capability make it a competitive analog alternative to traditional digital QPI methods.
A proof-of-concept experiment validated the approach, demonstrating successful imaging of distinct phase objects at different axial positions in the terahertz spectrum. The scalable nature of the design allows it to be adapted to various parts of the electromagnetic spectrum, including the visible and infrared (IR) bands, using appropriate nano-fabrication methods. This paves the way for new phase imaging solutions integrated with focal plane arrays or image sensor arrays for efficient on-chip imaging and sensing devices.
This research has profound implications for multiple fields, including biomedical imaging, sensing, materials science, and environmental analysis. By providing a faster and more efficient method for 3D QPI, this technology can enhance the diagnosis and study of diseases, the characterization of materials, and the monitoring of environmental samples, among other applications. The development of this cutting-edge approach opens new possibilities for the future of imaging and sensing, driving advancements in both science and technology.
By Impact Lab
