PhUn-Net: ready-to-use neural network for unwrapping quantitative phase images of biological cells-Reference-Cited by-同舟云学术

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PhUn-Net: ready-to-use neural network for unwrapping quantitative phase images of biological cells

Published:2020-01-24 Issue:2 Volume:11 Page:1107
ISSN:2156-7085
Container-title:Biomedical Optics Express
language:en
Short-container-title:Biomed. Opt. Express

Author:

Dardikman-Yoffe Gili,Roitshtain Darina,Mirsky Simcha K.,Turko Nir A.,Habaza Mor,Shaked Natan T.

Funder

European Research Council

Clore Israel Foundation.

Publisher

The Optical Society

Subject

Atomic and Molecular Physics, and Optics,Biotechnology

Reference41 articles.

1. Quantitative optical phase microscopy

2. Refractive-index profiling of optical fibers with axial symmetry by use of quantitative phase microscopy

3. Review on methods of solving the refractive index–thickness coupling problem in digital holographic microscopy of biological cells

4. Optical imaging of cell mass and growth dynamics

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1. Phase unwrapping in digital holography based on SRDU-net;Optics Communications;2024-12

2. Automated phase reconstruction and super-resolution with deep learning in digital holography;Optics & Laser Technology;2024-09

3. PUDCN: two-dimensional phase unwrapping with a deformable convolutional network;Optics Express;2024-07-15

4. Dual-frequency phase unwrapping based on deep learning driven by simulation dataset;Optics and Lasers in Engineering;2024-07

5. InSAR-DLPU: A benchmark dataset for deep learning-based synthetic aperture radar interferometry phase unwrapping [Software and Data Sets];IEEE Geoscience and Remote Sensing Magazine;2024-06

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