The viruses used in this article are in the table below

The microscopic visualization of large-scale three-dimensional (3D) samples by optical microscopy requires overcoming challenges in imaging quality and speed and in big data acquisition and management. We report a line-illumination modulation (LiMo) technique for imaging thick tissues with high throughput and low background. Combining LiMo with thin tissue sectioning, we further develop a high-definition fluorescent micro-optical sectioning tomography (HD-fMOST) method that features an average signal-to-noise ratio of 110, leading to substantial improvement in neuronal morphology reconstruction. We achieve a >30-fold lossless data compression at a voxel resolution of 0.32 × 0.32 × 1.00 μm3, enabling online data storage to a USB drive or in the cloud, and high-precision (95% accuracy) brain-wide 3D cell counting in real time. These results highlight the potential of HD-fMOST to facilitate large-scale acquisition and analysis of whole-brain high-resolution datasets.

Figure 1. Automatic signal segmentation on a raw data block with 11,200 × 5,200 × 3,200 voxels.

In this study, the researchers report a line-illumination modulation (LiMo) technique for imaging thick tissues with high throughput and low background, combining LiMo with thin tissue section-ing, they further develop a high-definition fluorescent micro-optical sectioning tomography (HD-fMOST) method. This allows for acquisition of more information about neuronal morphology than previously possible.