Bayesian-based aberration correction and numerical diffraction for improved lensfree on-chip microscopy of biological specimens

摘要

Lensfree on-chip microscopy is an emerging imaging technique that can be usedto visualize and study biological specimens without the need for imaging lenssystems. Important issues that can limit the performance of lensfree on-chipmicroscopy include interferometric aberrations, acquisition noise, and imagereconstruction artifacts. In this study, we introduce a Bayesian-based methodfor performing aberration correction and numerical diffraction that accountsfor all three of these issues to improve the effective numerical aperture (NA)and signal-to-noise ratio (SNR) of the reconstructed microscopic image. Theproposed method was experimentally validated using the USAF resolution targetas well as real waterborne Anabaena flos-aquae samples, demonstratingimprovements in NA by ~25% over the standard method, and improvements in SNR of2.3 dB and 3.8 dB in the reconstructed image when compared to the reconstructedimages produced using the standard method and a maximum likelihood estimationmethod, respectively.