Quantitative cytoarchitectural phenotyping of deparaffinized human brain tissues: source data

This repository provides the numerical source data for the <i>Communications Biology</i> publication <i>‘Quantitative cytoarchitectural phenotyping of deparaffinized human brain tissues’ </i>by Di Meo, Sorelli et al.The dataset is organized into the following folders:<b>Figure4</b>: numerical source data for the boxplots and probability density distributions presented in Figure 4 (<i>Quantitative cytoarchitectural analysis of pediatric human brain specimens</i>).<b>LSFM_data</b>: light-sheet fluorescence microscopy (LSFM) data, including maximum intensity projections of multichannel LSFM acquisitions.<b>TPFM_data</b>: two-photon fluorescence microscopy (TPFM) data, further structured into the following subfolders:<b>raw_tpfm</b>: raw tiled TPFM tissue reconstructions<b>pixel_classification</b>: outputs from ilastik’s pixel classification workflow (supervised machine learning–based image enhancement).<b>object_classification</b>: outputs from ilastik’s object classification workflow, including class-wise object masks and quantitative cellular features.