Halo removal for high resolution white light diffraction phase imaging

Abstract

As a quantitative phase imaging method, white light diffraction phase microscopy is widely used in biological cell research. However, the white light diffraction phase microscopy system uses low coherence white light irradiation, resulting in halo effect around the object, cause their own expression is not clear, also cause the adjacent object phase information missing. The asymmetric U-Net network proposed in this paper can eliminate halo effect for high resolution white light diffraction phase images. Compared with the iterative deconvolution algorithm, the method based on deep learning greatly improves the work efficiency. Our samples include standard particle, blood red cells HeLa cells, and USAF phase-resolution plate. The effectiveness and robustness of the method are verified.