Lei Tian

Computational Microscopy Using Coded Illumination for Biomedical Imaging

PROJECT DESCRIPTION
This project aims to develop a computational microscope to address the need for high spatial and temporal throughput imaging technologies for scalable biomedical imaging. Traditional microscopy techniques suffer from the fundamental trade-off among imaging field of view (FOV), spatial resolution and speed, limiting the achievable imaging throughput to a few megapixels per second. Computational microscopy is a new approach that uses computation to circumvent physical limitations by jointly designing hardware and algorithms. It has huge potential in revolutionizing biomedical imaging, as demonstrated by several emerging techniques, such as on-chip holography, interferometric synthetic aperture microscopy and Fourier ptychography. Here we propose development of a new computational microscopy technique that permits high-speed Gigapixel imaging capability, providing high spatial resolution across a large FOV across an extended depth of focus.

LABORATORY MENTOR
Alex Matlock

RESEARCH GOALS
Demonstrate label-free, high-throughput microscopy using coded illumination combined with computational reconstruction techniques for large-scale biomedical imaging applications. The core of our technique is based on novel illumination hardware that enables flexible angular patterning using patterned illumination, and novel 3D differential phase contrast and Fourier ptychographic phase-retrieval algorithms to reconstruct super-resolved nanoscale multi-parametric information across a wide field-of-view with an extended depth-of-field.

LEARNING GOALS
• This project combines optical and optoelectronic instrumentation, image reconstruction and analysis, and microscopy experimental techniques.
• Concepts in optical imaging and microscopy, as well as signal processing techniques of solving linear inverse problems.
• With regards to the optical imaging and microscopy techniques, the student will advance their use and understanding of bright field, dark field, asymmetric illumination based differential phase contrast, and illumination-scanning based 3D phase microscopy.
• Instrumentation methods based on our novel custom-built computational microscope equipped with a programmable LED array illumination unit.
• Critical analytical and signal processing skills in solving inverse problems.

TIMELINE
Jun 6 – mid July: Assisting in the construction of the LED array microscope and data collection
Mid July – Aug 10: 3D reconstruction algorithm development

Learn more about Professor Tian on his faculty page.