Automated Cell Nuclei detection for Large-Volume Electron Microscopy of Neural Tissue

Volumetric electron microscopy techniques, such as serial block-face electron microscopy (SBEM), generate massive amounts of image data that are used for reconstructing neural circuits. Typically, this requires time-intensive manual annotation of cells and their connections. To facilitate this analysis, we study the problem of automated detection of cell nuclei in a new SBEM dataset that contains cerebral cortex, white matter, and striatum from an adult mouse brain. The dataset was manually annotated to identify the locations of all 3309 cell nuclei in the volume. We make both dataset and annotations available here.

This is a supplementary to the ISBI 2014 paper "Automated Cell Nucleus Detection for Large-Volume Electron Microscopy of Neural Tissue".