Archivo: Laura Waller on Computational Imaging with Nonlinear Inverse Problems

Description: Computational Imaging with Nonlinear Inverse Problems BIDS Data Science Lecture Series | May 1, 2015 | 1:00-2:30 p.m. | 190 Doe Library, UC Berkeley Speaker: Laura Waller, Assistant Professor, EECS, Berkeley Sponsors: Berkeley Institute for Data Science, Data, Society and Inference Seminar Computational imaging involves the joint design of optical systems and post-processing algorithms such that computation replaces optical elements, enabling simple experimental setups. This talk will describe new optical microscopes that employ simple experimental architectures and efficient nonlinear inverse algorithms to achieve high-resolution 3D and phase images. By leveraging recent advances in computational illumination, we achieve brightfield, darkfield, and phase contrast images simultaneously, with extension to 3D and gigapixel phase imaging. We discuss unique challenges for large-scale real-time imaging of biological samples in vitro and in vivo.
Title: Laura Waller on Computational Imaging with Nonlinear Inverse Problems
Credit: Computational Imaging with Nonlinear Inverse Problems at 44:52, cropped
Author: Berkeley Institute for Data Science (BIDS)
Usage Terms: Creative Commons Attribution 3.0
License: CC BY 3.0
License Link: https://creativecommons.org/licenses/by/3.0
Attribution Required?: Yes