Quantitative AFM Image Analysis

Quantitative AFM Image Analysis is a measurement service. You send atomic force microscopy images. You receive the measurement you asked for, as a distribution with summary statistics, alongside the per-object data behind it and a manifest recording which files went in, which pipeline version ran, and which objects were excluded and why.

It is used by research groups needing a measurement nobody in the lab performs, by core facilities offering an analysis capability they cannot staff, by contract laboratories adding an analysis line to imaging they already sell, and by industry programs that need quantified morphology and size distributions as an endpoint with a documented method.

Why the numbers hold

Three things this buys you

Statistical power

Measurement across thousands of objects rather than the dozens a person can hand-measure. Distribution shape, heterogeneity and rare subpopulations only become visible at that scale.

Reproducibility

The same inputs and the same pipeline version produce the same numbers every time, with the parameters recorded alongside the result.

Defensibility

Every reported number traces back to the image it came from. A reviewer, a collaborator or an auditor can follow the path from raw file to reported figure.

How it works

Engagements run in two stages. The first exists so that the second can be quoted at a firm price, on work that otherwise varies considerably from job to job.

Stage 1: Feasibility assessment
You send 10 to 20 representative images. The pipeline is run against them to establish whether the measurement can be made on this sample type. You receive a short written assessment covering whether the measurement is possible, the expected number of measurable objects, any problems with the data, and a firm fixed-price quote for the full run.
You find out cheaply whether your data can support the question you are asking, before committing to a full project.
$500, credited in full against the project if you proceed.
Stage 2: Full analysis
Begins once the quote is accepted. Inputs are frozen on receipt. The pipeline runs with its version and parameters recorded, detections are reviewed against fixed QC criteria, and the deliverable package is produced. Results reference the input manifest, so any number in the report traces back to a specific file.

Method development and training engagements are scoped individually and do not follow this two-stage path.

What a project includes

Work scales with the number of objects measured rather than the number of files, so one project is defined by a ceiling on both, whichever is reached first.

One project covers up to 40 images or not-used measured objects, whichever is reached first. Datasets beyond this are quoted as multiple units, or at a per-image rate set in the quote.

Included in a project

One measurement set as defined in the accepted quote.
QC review against fixed criteria.
The distribution and summary statistics.
The PDF report.
The per-object CSV.
The run manifest.
One round of revisions covering clarification and presentation.

Quoted separately

These are not included. They are listed here so the boundary is clear before a project starts rather than after.

Additional measurands not in the original quote.
Re-running after additional images are supplied.
Statistical comparison against conditions not named at quoting.
Figure restyling for journal submission.
Response-to-reviewer analysis.

Data that cannot be measured

Some images cannot be measured. The usual reasons are:

Resolution falls below the pixel-size floor.
Object density is too high to separate reliably.
Substrate contamination exceeds threshold.
Files are damaged or incomplete.

Where a defined proportion of a dataset fails, delivery proceeds on the measurable portion and the remainder is reported rather than discarded. The exclusion count and the criterion that produced it appear in every report.

Exclusions are always counted and always reported. Data is never silently dropped or filtered.

Where more than 10% of a dataset cannot be measured, work pauses and you are consulted before it continues, rather than a partial result being delivered as though it were complete.

Turnaround

Projects are delivered within one week of receiving the complete dataset. Turnaround is quoted from receipt of the complete dataset, not from first contact, and the clock pauses while awaiting decisions or clarification.

What you receive

Deliverables

Every project returns three artifacts.

PDF report

Figures, summary statistics, and the methods section describing what was measured and how.

Per-object CSV

Every individual measurement, not just the summary. You can reanalyse the distribution yourself, apply your own cutoffs, or combine it with other data.

JSON run manifest

Input file hashes, pipeline version, every parameter used, and every exclusion with its reason. This is what makes a result checkable months later.

Reports are versioned. A revised report is issued as a new version and never overwrites the one you already have.

Formats and requirements

Accepted formats

Tested end to end:

Bruker NanoScope
Asylum Research IBW
NT-MDT
Gwyddion (.gwy)

Most other instrument formats can be supported. If yours is not listed, say so in your enquiry. Whether it can be read is confirmed during the feasibility assessment, before you commit to a full project.

Image requirements

Measurability is set by object size relative to pixel size rather than by any absolute figure. As a working rule, an object needs to span roughly four to five pixels across before its size can be measured reliably, so pixel size should be no larger than about a quarter of the smallest feature of interest. Below that, the measurement floors out and small objects are lost rather than mismeasured.

Raw or minimally processed data is preferred, with any flattening already applied recorded. Height measurements depend on the background definition, so an undocumented flattening step cannot be undone or accounted for.

What cannot be measured

What can and cannot be measured depends on the measurement being requested and on the quality of both the imaging and the sample. The feasibility assessment exists to answer that question against your actual data rather than in the abstract. Some cases are known in advance:

Exported PNG or TIFF images. These carry a picture of the surface rather than the height data every measurement here depends on. Raw instrument files are needed.
Objects below the pixel-size floor for the requested measurement. They are not mismeasured, they are not detected at all, and their absence shifts the distribution.
Fields crowded enough that touching objects cannot be separated reliably. Fused neighbours inflate both the large end of a size distribution and the apparent elongation of the objects in it.
Absolute height where no flattening record exists. Relative comparisons within a consistently processed dataset remain valid.
Comparisons pooled across substrates or imaging sessions with different backgrounds and detection floors. These are reported separately rather than combined.

Engagement types

Project analysis

One condition set measured against an agreed definition, returned as a report with the per-object data and run manifest. The two-stage path above applies.

Method development

Building and validating a measurement pipeline for a specific assay where none currently exists. Scoped individually, with validation criteria agreed before work starts.

Training

Workshops on quantitative AFM analysis, covering measurement definition, detection review, and how to report distributions defensibly. Quoted by format and location.

Pricing

Prices are published as a structure and a floor rather than a rate card. Jobs differ in object count, image quality, sample type and the number of measurands requested, so a published table would be wrong for most visitors. The feasibility assessment exists so that a firm fixed price can be given once the data has been seen.

Feasibility assessment	$500, credited toward the project
Project analysis, academic	from $1,500
Method development	from $4,000
Training and workshops	$1,200 per day
LabTools, academic and individual	Free
Core facility site license	Institutional pricing on enquiry
Commercial and industry work	Quoted after assessment

All projects are subject to a minimum of $1,500.

What changes a quote

Three broad categories, in increasing order of effort:

Standard: The measurement is one the pipeline already performs on this sample type.
Non-standard: The pipeline requires parameter tuning or adaptation for the sample.
Development: The measurement does not yet exist and must be built and validated. Scoped as a separate engagement.

What the estimate is based on

The number of objects to be measured.
Whether the sample type is already supported.
How much manual review the detections require.
How many distinct measurands are requested.

Published figures are starting points subject to assessment, not fixed rates. All projects are subject to the stated minimum.

Confidentiality

Client data is held in access-scoped storage. It is not used for any purpose other than the engagement without written agreement. Raw inputs are retained for a defined period after delivery and then removed.

Raw inputs are retained for 90 days after delivery and then removed.

An NDA can be put in place on request before any data is sent.

Start a feasibility assessment

Tell me what you are trying to measure and roughly what data you have. You will get a reply saying whether the measurement is feasible, what the feasibility assessment would involve, and what it would cost.

Request a quote to begin, or see how to send data if an assessment is already agreed.