Developments of infrared-pump visible-probe phase imaging on chemical selectivity and deep-learning enhancement

Abstract

Optical phase microscopy is widely adopted for quantitative imaging of optical density in transparent cells and tissues, yet lacks the chemical selectivity. To address this challenge, a bond-selective transient phase imaging (BTSP) technique was developed, in which a transient change in phase induced by infrared excitation of molecular vibrations was detected by a diffraction phase microscope. BTSP achieved chemically selective phase imaging of live cells. We further demonstrated an IR-pump visible-probe phase microscopy based on second harmonic generation after the sample, enabled by deep learning. The phase-sensitive information is encoded into the second harmonic signal, which is decoded using a deep learning algorithm. It presents a label-free technique featured by high phase sensitivity and high robustness against noises, which has promising applications in biological and medical imaging and remote sensing.