StereoMate

StereoMate performs automated stereological analysis of immunofluorescently labelled cleared tissue images to extract unbiased object-level 3D quantitative data for studying tissue and cellular organization.

Key Features:

• Automated Image Segmentation: Implements validated segmentation protocols to identify structures in immunofluorescent images of cleared tissues.
• Stereological Analysis: Employs stereological techniques to derive unbiased 3D quantitative measurements at the object level.
• Object-level Data Generation: Produces object-level 3D quantitative datasets representing individual structures within cleared tissues.
• Validated Segmentation Protocols: Segmentation protocols are rigorously validated to ensure accurate extraction of immunofluorescent signal from cleared specimens.

Scientific Applications:

• Dorsal Root Ganglion Neuron Morphometry: Validated on mouse dorsal root ganglion neurons to detect significant changes in neuronal size and structure.
• Spinal Dorsal Horn Injury Analysis: Identifies loss of axonal input and synaptic terminations within the spinal dorsal horn following injury.
• 3D Quantitative Analysis of Cleared Immunofluorescence: Generates datasets for analysis of tissue organization and cellular interactions in cleared, immunofluorescent specimens.

Methodology:

Validated image segmentation protocols are applied to immunofluorescent images of cleared tissues, and automated stereological methods extract unbiased object-level 3D quantitative data.