Time of Travel
The travel time of reflected photons, ballistic photons (photons which interacted with the tissue only once), and heavily scattered photons is different. Though this time difference is very small, advances in the imaging speeds allow us to differentiate the nature of the photons at the sensor. Therefore, we propose to tag the photons based on their time-of-travel. In the past, the team has developed a set of imaging systems and algorithms that measure the time-of-travel of the photons.
This project allows us to see through scattering materials using ultra-fast imaging. The method uses the entire optical signal leading to a new approach called “All Photon Imaging”. Photons with different time-of-travel suffer different degradations (blur). Hence, by separating the photons based on the travel-time and deblurring them separately, the API computationally images through the scattering medium. The proposed technique finds applications in medical imaging, seeing through fog, and seeing through other obstructive materials.
This project demonstrates a new method to detect and distinguish different types of fluorescent materials.
The project develops a camera that can look around corners and beyond the line of sight. The camera uses light that travels from the object to the camera indirectly, by reflecting off walls or other obstacles, to reconstruct a 3D shape.
This project explores the question of whether “phase based Time of Flight (ToF) range cameras can be used for looking around corners and seeing through scattering diffusers.
The project describes a new imaging system that can read through the pages of a closed book. This system has applications in industrial inspection and in history and preservation, allowing us to read through closed antique documents or inspect samples of cultural value.
The project – Blind and Reference-free Fluorescence Lifetime Estimation via Consumer Time-of-Flight Sensors, outlines a novel, cost-effective solution for fluorescence lifetime imaging (FLI). Fluorescence lifetime imaging (FLI) is a well-established imaging parameter that finds important applications across several areas of life sciences. Examples include DNA sequencing, malignant tumor detection and super-resolution microscopy. Generally, FLI is performed using sophisticated electro-optical instruments which are expensive and cost in the range of several thousands of dollars. This work shows that it is possible to trade-off the precision of electro-optical instruments with sophistication in computational methods used for lifetime estimation purposes. To this end, our team members repurpose low-cost, time-of-flight or ToF sensors (e.g., Microsoft Kinect) for FLI.