Artifact-free whole-slide imaging with structured illumination microscopy and Bayesian image reconstruction

Area of Science:

• Biomedical Imaging
• Histopathology
• Optical Microscopy

Background:

• Structured illumination microscopy (SIM) offers optical sectioning and super-resolution capabilities for biological samples.
• Optimized imaging setups and data processing minimize artifacts in SIM.
• Bayesian estimation aids in reconstructing images with resolution exceeding optical limits.

Purpose of the Study:

• To present high-quality, artifact-free panoramic SIM images of human tissues.
• To showcase the utility of SIM in visualizing pathophysiological conditions.
• To provide valuable datasets for advancing fluorescent histopathology.

Main Methods:

• Acquisition of large panoramic SIM images of human tissue samples.
• Imaging of various cancers (prostate, skin, ovary, breast) and tuberculosis.
• Utilizing standard histological preparations stained with hematoxylin-eosin.

Main Results:

• High-quality, artifact-free SIM images were generated for diverse human tissues.
• Successful imaging of cancers and tuberculosis demonstrates SIM's diagnostic potential.
• Five complete datasets of panoramic SIM images are presented.

Conclusions:

• SIM is a valuable tool for histopathology, reducing artifacts common in fluorescence microscopy.
• Stitched SIM images show promise for intraoperative histology.
• The release of high-quality SIM data will accelerate research in fluorescent histopathology.