Single-shot multispectral quantitative phase imaging using deep neural network

TL;DR

This paper introduces a novel single-shot multispectral quantitative phase imaging method that employs a deep neural network to generate multi-wavelength phase maps from a single interferogram, simplifying the process and enhancing spectroscopic capabilities.

Contribution

The authors develop a deep neural network-based framework that enables single-shot multispectral phase imaging, reducing measurement complexity and improving chemical specificity in QPI.

Findings

Successfully trained GAN to generate multi-spectral phase maps from single interferograms.

Validated the method on optical waveguides and osteosarcoma cells, showing accurate phase reconstruction.

The framework enhances spectroscopic QPI without complex instrumentation.

Abstract

Multi-spectral quantitative phase imaging (MS-QPI) is a cutting-edge label-free technique to determine the morphological changes, refractive index variations and spectroscopic information of the specimens. The bottleneck to implement this technique to extract quantitative information, is the need of more than two measurements for generating MS-QPI images. We propose a single-shot MS-QPI technique using highly spatially sensitive digital holographic microscope assisted with deep neural network (DNN). Our method first acquires the interferometric datasets corresponding to multiple wavelengths ({\lambda}=532, 633 and 808 nm used here). The acquired datasets are used to train generative adversarial network (GAN) to generate multi-spectral quantitative phase maps from a single input interferogram. The network is trained and validated on two different samples, the optical waveguide and a MG63 osteosarcoma cells. Further, validation of the framework is performed by comparing the predicted phase maps with experimentally acquired and processed multi-spectral phase maps. The current MS-QPI+DNN framework can further empower spectroscopic QPI to improve the chemical specificity without complex instrumentation and color-cross talk.