10x more cells, one new standard: Complete Blood Morphology®

Complete Blood Morphology (CBM®) is set to transform routine blood smear review to be fully autonomous, standardized and unlock deeper diagnostic insights.

From CBC to CBM to OMG.

A defining moment for hematology,
resolving industry-wide challenges

Lack of standardization
across staff, shifts and locations 

Staffing shortages create gaps
and costly training cycles

Manual inefficiency in otherwise
automated lab environments

Full-Field makes the
impossible possible.

Operating downstream of your CBC analyzer, CBM® uses Scopio’s exclusive Full-Field imaging and AI to detect, classify and quantify thousands of blood cells, eliminating the need for manual review in routine cases.

That vastly expanded sample size delivers 10 times more data than the current diagnostic standard.

Complete Blood Morphology (CBM®) Analyzer*

CBM® will bring true end-to-end automation to the lab while
unlocking new diagnostic potential.

Autonomous Review

Designed to deliver hands-off review for routine cases from scan to final report.

Process Standardization

Delivering consistent and quantitative results across shifts and labs.

Staffing Optimization

Reducing hiring pressures and freeing up tech staff for complex cases.

Advanced Diagnostics

Morphology-based biomarkers for early detection and action, untapped diagnostic potential.

Routine morphology will never be the same

Integrate your CBC with CBM® to get a labor free process, from
scan to final report

Supersize your analysis with 10x more cells

With 10x more cells per slide, analyzed at the speed of AI, CBM® will deliver statistical power no human can match, supporting more confident clinical decisions.

1,000 WBCs

Across 20 parameters

10,000 RBCs

Across 25 parameters

5X FOVs

For platelet evaluation
across 6 parameters

Your hematology lab workflow has hit a wall.
How do you break through?

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*Scopio Labs’ CBM® is under development and not available for in vitro diagnostic use

**Actual cell counts may vary depending on sample characteristics.