3D reconstruction of a hologram with brightfield contrast using deep learning

Yichen Wu; Yilin Luo; Gunvant Chaudhari; Yair Rivenson; Kevin De Haan; Ayfer Calis; Aydogan Ozcan

doi:10.1117/12.2567300

20 August 2020 3D reconstruction of a hologram with brightfield contrast using deep learning

Yichen Wu, Yilin Luo, Gunvant Chaudhari, Yair Rivenson, Kevin De Haan, Ayfer Calis, Aydogan Ozcan

Proceedings Volume 11469, Emerging Topics in Artificial Intelligence 2020; 1146919 (2020) https://doi.org/10.1117/12.2567300
Event: SPIE Nanoscience + Engineering, 2020, Online Only

Abstract

Holographic microscopy encodes the 3D information of a sample into a single hologram. However, holographic images are in general inferior to bright-field microscopy images in terms of contrast and signal-to-noise ratio, due to twin-image artifacts, speckle and out-of-plane interference. The contrast and noise problem of holography can be mitigated using iterative algorithms, but at the cost of additional measurements and time. Here, we present a deep-learning-based cross-modality imaging method to reconstruct a single hologram into volumetric images of a sample with bright-field contrast and SNR, merging the snapshot 3D imaging capability of holography with the image quality of bright-field microscopy.

Conference Presentation

Citation Download Citation

Yichen Wu, Yilin Luo, Gunvant Chaudhari, Yair Rivenson, Kevin De Haan, Ayfer Calis, and Aydogan Ozcan "3D reconstruction of a hologram with brightfield contrast using deep learning", Proc. SPIE 11469, Emerging Topics in Artificial Intelligence 2020, 1146919 (20 August 2020); https://doi.org/10.1117/12.2567300

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available