Only Cellairus provides automatic, accurate, unbiased, high-throughput 3D cell quantification in fluorescently-labeled histological specimens.
Unbiased stereology is recognized as the gold standard for accurate quantification because it is a rigorous and accurate methodology for quantifying features of biological tissues. Cellairus dramatically accelerates stereological cell counting through the use of machine learning to replicate expert human observer judgments of about recognizing cells, their location and size. Once the machine learning algorithms are trained, Cellairus identifies cells in 3D image volumes throughout 3D brain regions using the same observer criteria as a human expert. Cellairus has been developed by the leading experts in stereology to preserve the integrity and benefits of stereology, while substantially reducing the amount of time needed to perform accurate quantification cell populations.
Cellairus uses state-of-the-art machine learning techniques, integrated with unbiased stereological counting rules, systematic random sampling (SRS) unbiased stereological sampling, and easy to learn workflows to classify, and quantify cells in 3D images. Cellairus automates the most widely used unbiased stereological probe for counting cells, the optical fractionator.
Using the defined counting frame, grid size and disector parameters, Cellairus detects all cells at each counting site. Once all objects are automatically detected within each counting frame site; the counting rules are then applied to filter and only retain the detected cells that fall within the disector.
Cellairus can be trained to differentiate between different cells types, sub-cellular objects and non-cell objects. To accommodate varying neuron densities in different brain regions, machine learning classifiers can be trained on both dense and sparse neuron populations. Entire studies are rapidly processed.
Download Cellairus product sheet here.
To avoid bias from standard image segmentation and thresholding techniques, we developed an intelligent automated parameter estimation process. This algorithm analyses individual subvolumes with high numbers of objects and optimizes key segmentation parameters to best match objects’ structure.
Objects are automatically detected in 3D within each counting frame site, the unbiased counting rules are then applied to only count the detected cells that fall within the optical disector. The well-established mathematical formulae used in design based stereology are then applied to produce statistically robust results about cell population that are assessed for accuracy using stereological coeffect of error estimates.
MBF products are used across the globe by the most prestigious laboratories.
MBF’s software utility is underscored by the number of references it receives in the worlds most important scientific publications.
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The C2 and PH domains of CAPS constitute an effective PI(4,5)P2-binding unit essential for Ca2+-regulated exocytosisView Publication
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Oral Treatment with the Extract of Euterpe oleracea Mart. Improves Motor Dysfunction and Reduces Brain Injury in Rats Subjected to Ischemic StrokeView Publication
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Hippocampal vulnerability to hyperhomocysteinemia worsens pathological outcomes of mild traumatic brain injury in ratsView Publication
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Dopamine transporter and synaptic vesicle sorting defects underlie auxilin-associated Parkinson’s diseaseView Publication
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Neonatal loss of FGFR2 in astroglial cells affects locomotion, sociability, working memory, and glia-neuron interactions in miceView Publication
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Brain injury accelerates the onset of a reversible age-related microglial phenotype associated with inflammatory neurodegenerationView Publication
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Adolescent exposure to low-dose Δ9-tetrahydrocannabinol (THC) depletes the ovarian reserve in female miceView Publication
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"Transforming representations of movement from body- to world-centric space."
Yes, it works with multichannel fluorescent images.
Yes, you are able to audit and inspect the results to assess the accuracy using the dynamic 3D visualization environment.
Yes, different classifiers can be trained for different types of cells or imaging methos. Cellairus is shipped with some classifiers built in. You can even contract training for your specific experiments to us and we will train the classifier for you.
Yes, the results will be computed using established stereological formulas.
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Our service sets us apart, with a team that includes Ph.D. neuroscientists, experts in microscopy, stereology, neuron reconstruction, and image processing. We’ve also developed a host of additional support services, including:
At MBF, we’ve spent decades understanding the needs of researchers and their labs — and have a suite of products and solutions that have been specifically designed for the needs of today’s most important and advanced labs. Our commitment to you is to spend time with you discussing the needs of your lab — so that we can make sure the solutions we provide for you are exactly what you’ll need. It’s part of our commitment to supporting you — before, during, and after you’ve made your decision. We look forward to talking with you!
The complete stereology solution. The gold standard for unbiased cell counting.
The gold standard in unbiased stereology for use on cleared tissue.
Unbiased stereology for whole slide images. Specially designed for analyzing large whole slide images.