MBF Bioscience NeuroInfo brain mapping software
NeuroInfo software from MBF Bioscience is used for automatically aligning serial sections and mapping brain volumes and cell counts to a standardised reference space.
Identification and delineation of brain regions in histologic mouse brain sections is pivotal for many neurogenomics, transcriptomics, proteomics and connectomics studies, yet this process is usually manual and prone to observer error and bias. NeuroInfo automatically navigates researchers through the complex microscopic anatomy of histologic sections of mouse brains, eliminating much of the user’s potential for error. It works with specimens imaged with brightfield, confocal and widefield fluorescence and yields repeatable, objective anatomic data for understanding the organisation and composition of the nervous system.
Users can perform identification and delineation of brain regions in experimental mouse-brain sections, utilise automatic cell detection that uses deep learning to recognise and count specific neuronal subtypes, and perform optimisations that result in up to 10x faster registration, mapping and display of detected cells. The software replaces the tedious manual process of neuroanatomical identification, so there is no need to page through a reference atlas to match experimental images or manually delineate anatomies in images.
The product aligns whole slide images of experimental tissue sections to the Allen Mouse Brain Atlas, aggregates measurements from within anatomical regions and detected cells can be tallied in each of its 2500 brain structures, making comparative quantitative analysis between mice from different experiments and laboratories easy and standardised. Its deep learning algorithms are robust against histologic and imaging artifacts such as edge effects, uneven illumination and variable staining across specimens. Its calibration tool also allows the registration of sections cut in any orientation (coronal, sagittal or horizontal). It accommodates differences in histological processing between laboratories so that it is applicable to the work performed in many laboratories.
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