ArticleMethods in molecular biology (Clifton, N.J.)2026
A Computational Protocol for Whole Brain Histology Imaging.
Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Recent advancements in tissue clearing and multiplex labeling have enabled the rapid acquisition of high-resolution, whole-brain 3D imagery [3]. However, the resulting datasets are often massive in size and structurally complex, creating significant bottlenecks in data storage, processing, and analysis. Here, we propose a robust, end-to-end pipeline designed to manage and analyze these large-scale volumes efficiently. This protocol utilizes a chunk-based data structure (OME-Zarr) to drastically lower hardware memory requirements [2], enabling the processing of terabyte-scale data on standard workstations. We design a workflow that integrates artifact correction, automated deep learning segmentation, and atlas registration. Furthermore, the pipeline facilitates dynamic, multiscale 3D visualization via a web-based interface (Neuroglancer) [7], allowing for the remote exploration of massive datasets without the need for complete data transfer.
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