- Tytuł:
- Phase retrieval without phase unwrapping for white blood cells in deep-learning phase-shifting digital holography
- Autorzy:
-
Jin, Shuyang
Xu, Xiaoqing
Chen, Jili
Ni, Yudan - Powiązania:
- https://bibliotekanauki.pl/articles/2202768.pdf
- Data publikacji:
- 2023
- Wydawca:
- Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
- Tematy:
-
digital holography
phase retrieval
deep learning - Opis:
- Phase retrieval and phase unwrapping are the two important problems for enabling quantitative phase imaging of cells in phase-shifting digital holography. To simultaneously cope with these two problems, a deep-learning phase-shifting digital holography method is proposed in this paper. The proposed method can establish the continuous mapping function of the interferogram to the ground-truth phase using the end-to-end convolutional neural network. With a well-trained deep convolutional neural network, this method can retrieve the phase from one-frame blindly phase-shifted interferogram, without phase unwrapping. The feasibility and applicability of the proposed method are verified by the simulation experiments of the microsphere and white blood cells, respectively. This method will pave the way to the quantitative phase imaging of biological cells with complex substructures.
- Źródło:
-
Optica Applicata; 2023, 53, 1; 127--140
0078-5466
1899-7015 - Pojawia się w:
- Optica Applicata
- Dostawca treści:
- Biblioteka Nauki
Artykuł