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Generative deep learning-enabled ultra-large field-of-view lens-free imaging
March 18, 2024, 4:46 a.m. | Ronald B. Liu, Zhe Liu, Max G. A. Wolf, Krishna P. Purohit, Gregor Fritz, Yi Feng, Carsten G. Hansen, Pierre O. Bagnaninchi, Xavier Casadevall i Solva
cs.CV updates on arXiv.org arxiv.org
Abstract: Advancements in high-throughput biomedical applications necessitate real-time, large field-of-view (FOV) imaging capabilities. Conventional lens-free imaging (LFI) systems, while addressing the limitations of physical lenses, have been constrained by dynamic, hard-to-model optical fields, resulting in a limited one-shot FOV of approximately 20 $mm^2$. This restriction has been a major bottleneck in applications like live-cell imaging and automation of microfluidic systems for biomedical research. Here, we present a deep-learning(DL)-based imaging framework - GenLFI - leveraging generative artificial …
abstract applications arxiv biomedical capabilities cs.cv deep learning dynamic fields free generative imaging limitations major optical physics.optics real-time systems type view
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