Object Count (General)
Count cells, bacteria, and particles in any image
Example outputs shown for illustration. Numbers depend on your samples and protocol.
Results
Each measurement below comes from your own images, tied back to the annotated frame it came from, so results stay comparable across samples, locations, and conditions.
µm or count
Object count
Size and shape measured for every detected object, then summarized across the population.
In your report: Per-object table, size distribution, and summary percentiles.
µm or count
Size distribution
Size and shape measured for every detected object, then summarized across the population.
In your report: Per-object table, size distribution, and summary percentiles.
per area
Object density
Findings placed in sample coordinates to reveal spatial patterns and local density.
In your report: Coordinate-referenced map, regional density, and representative images.
Built around your image set
Use the calibrated images your team already collects, together with the locations you need to compare.
Each report includes
The artifacts your team receives, ready for review and archive.
Annotated image set
Original images with regions of interest, measurement points, masks, and finding overlays.
Measurement table
Location-indexed values, units, distributions, and QC flags in a structured export.
Method record
Calibration evidence, analysis settings, version history, and validation summary.
Confidence in every resultTraceable measurements, reviewed against your agreed reference method.
- Traceable scale
- The report records the image scale, calibration evidence, and a method-specific expanded measurement uncertainty. It does not use one product-wide accuracy number.
- Reference comparison
- The configured method is compared with your accepted reference method or reviewed annotations, and reports bias by measurement range and image condition.
- Detection performance
- Detections are evaluated against reviewed reference regions with precision, recall, and segmentation overlap, separated by the conditions that affect performance.
- Repeatability
- The locked protocol is rerun on the same inputs and on a defined repeat set. The review records variation from image acquisition, sampling, and analysis separately where possible.
From image to reviewed result
- 1
Upload
Load images with countable objects
- 2
Configure
Set detection sensitivity and size range
- 3
Count
AI identifies and counts objects
- 4
Export
Download counts, size distributions, and annotated images
Built to handle your images
What the analysis does with the awkward cases — the reasons the numbers above hold up on real microscopy.
Scale-Agnostic Detection
Works from microscopic assay objects to macroscopic particles — one algorithm, any magnification
Size and Shape Filtering
Set minimum/maximum size gates and circularity thresholds to exclude irrelevant objects
Spatial Statistics
Generate nearest-neighbor distances, clustering indices, and spatial distribution maps
Works with your existing tools
Object Count (General) with ConductVision Image
General-purpose counting software that identifies and measures discrete objects in any microscopy or macroscopy image you upload. ConductVision’s detection handles cells, bacteria, beads, particles, crystals, and other countable features with adjustable sensitivity and size filtering. It is image-analysis software, not a dedicated cell-counting machine or particle counter instrument.
Not sure this is the right measurement?
Send a representative image and your measurement goal. A ConductVision scientist will confirm whether this is the right fit, or point you to the closer workflow, before you commit to a quote.
Questions & answers
The questions scientists ask before sending a sample set. If yours is not here, ask a scientist directly.
Is this a cell counting machine or software?
It is software. ConductVision counts objects in images you upload from your own microscope or camera, so there is no separate counting instrument to buy or calibrate.
What can the general object counter count?
Cells, bacteria, beads, particles, crystals, and other discrete features. You set a size range and shape gates so the detector keeps the objects you care about and ignores the rest.
How do I count objects in a microscopy image?
Upload the image, set detection sensitivity and a size range, let the AI count, then export counts, size distributions, and an annotated overlay. The same settings can be locked and reused across a batch of images.
Send a sample image and a measurement goal
We will show the closest ConductVision workflow and flag what needs custom validation for your images.
