No-search focus prediction at the single cell level in digital holographic imaging with deep convolutional neural network.

Clicks: 315
ID: 20274
2019
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Ranked #9 of 18 articles by views in Biomedical optics express

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Abstract
Digital propagation of an off-axis hologram can provide the quantitative phase-contrast image if the exact distance between the sensor plane (such as CCD) and the reconstruction plane is correctly provided. In this paper, we present a deep-learning convolutional neural network with a regression layer as the top layer to estimate the best reconstruction distance. The experimental results obtained using microsphere beads and red blood cells show that the proposed method can accurately predict the propagation distance from a filtered hologram. The result is compared with the conventional automatic focus-evaluation function. Additionally, our approach can be utilized at the single-cell level, which is useful for cell-to-cell depth measurement and cell adherent studies.
Reference Key
jaferzadeh2019nosearchbiomedical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jaferzadeh, Keyvan;Hwang, Seung-Hyeon;Moon, Inkyu;Javidi, Bahram;
Journal Biomedical optics express
Year 2019
DOI
10.1364/BOE.10.004276
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