Evaluation of tile artifact correction methods for multiphoton microscopy mosaics of whole-slide tissue sections

Abstract

Multi-photon microscopy (MPM) is a useful biomedical imaging tool due, in part, to its capabilities of probing tissue biomarkers at high resolution and with depth-resolved capabilities. Automated MPM tile scanning allows for whole-slide image acquisition but suffers from tile-stitching artifacts that prevent accurate quantitative data analysis. We have investigated a variety of post-processing artifact correction methods using ImageJ macros and custom Python/ MATLAB code and present a quantitative and qualitative comparison of these methods using whole-slide MPM autofluorescence images of human duodenal tissue. Image quality is assessed via evaluation of artifact removal compared to the calculated mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM) of the processed image and its raw counterpart. Consideration of both quantitative and qualitative results suggest a combination of flat-field based correction and frequency filtering processing steps provide improved artifact correction when compared to each method used independently to correct for tiling artifacts of tile-scan MPM images. © 2022 SPIE.