Physics-constrained computational imaging

Laura Waller

doi:10.1117/12.2571478

2 September 2020 Physics-constrained computational imaging

Laura Waller

Proceedings Volume 11469, Emerging Topics in Artificial Intelligence 2020; 114690M (2020) https://doi.org/10.1117/12.2571478
Event: SPIE Nanoscience + Engineering, 2020, Online Only

Abstract

Computational imaging involves the joint design of imaging system hardware and software, optimizing across the entire pipeline from acquisition to reconstruction. Computers can replace bulky and expensive optics by solving computational inverse problems. This talk will describe end-to-end learning for development of new microscopes that use computational imaging to enable 3D fluorescence and phase measurement. Traditional model-based image reconstruction algorithms are based on large-scale nonlinear non-convex optimization; we combine these with unrolled neural networks to learn both the image reconstruction algorithm and the optimized data capture strategy.

Conference Presentation

Citation Download Citation

Laura Waller "Physics-constrained computational imaging", Proc. SPIE 11469, Emerging Topics in Artificial Intelligence 2020, 114690M (2 September 2020); https://doi.org/10.1117/12.2571478

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