Automated Extraction of in Vivo Calcium Signals From Light-sheet Fluorescence Microscopy

Master's Defense
Speaker Name
Jun Jiang
Date and Time
-
Location
Talk will be remote on Zoom
Abstract

The automotive industry is a driver of global economic development, acting as a force of scientific research and technological innovation. In the 21st century, this industry is on the cusp of revolutionary change with the emergence of self-driving vehicles. Without human oversight, these autonomous vehicles operate with the assistance of cameras, sensors, and software. Currently, AD generally suffers from bad vision in low-light conditions, especially from the glares of other vehicles. To solve this issue, a video processing algorithm and a simple lighting configuration are proposed, based on the lock-in detection principle. This can be implemented not only in software, but also in all hardware (using multi-channel locking amplifiers) for fast speed. We applied our algorithm to the images from two experiments and demonstrated that this method successfully suppressed the glares and improved the identification of objects. Our approach can be easily integrated into current autonomous vehicles and enhances safety by providing clearer images in low light conditions.

Zoom link: https://duke.zoom.us/j/4950774435

Host
Advisor: Neil Gong Committee: Rong Ge, Roark Horstmeyer