Ingest
Raw instrument files are frozen on receipt. Every input is hashed and listed in the manifest.
sha256 · 38 inputs
Automated AFM image analysis
Your microscopy images, measured at scale. Every number traceable.
Filliaux Industries runs automated measurement pipelines on atomic force microscopy data. You send images. You receive distributions with statistics, the per-object data behind them, and a manifest of exactly how every number was produced.
Request a quote How the pipeline works
Reads
- Bruker NanoScope
- Asylum IBW
- NT-MDT
- Gwyddion
Returns
- PDF report
- per-object CSV
- JSON manifest
Objects detected 0/ 38 images
QC · exclusions —
1000sObjects measured per dataset, not dozens
100 %Of exclusions counted and reported
1 weekTurnaround from the complete dataset
3 filesReport, per-object CSV, run manifest
The pipeline
Five stages. Zero hand-measuring.
The same versioned pipeline runs on every dataset, so the same inputs give the same numbers, every time.
Detect
Objects are segmented from the height field with a fixed, versioned detector. No hand-picking.
1 903 candidates
Measure
Every object gets the same measurement set: height, volume, length, position, morphology.
per-object CSV
QC
Detections are reviewed against fixed criteria. Exclusions are counted, never silently dropped.
61 excluded · reasons logged
Report
Distribution, statistics and a methods section. Versioned, and traceable to each input file.
PDF · CSV · JSON
See it work
From raw height field to defensible result
Drag the divider. The left side is what the instrument produced. The right side is what comes back: every object detected, measured, and either passed or excluded for a stated reason.
Raw height image Detected + measured
$ labtools analyze --pipeline particle-size@2.4.1 ./B2_run/ ✓ ingest 38 files · 38 hashes recorded ✓ detect 1 903 candidates ✓ measure height · volume · diameter ✓ qc 61 excluded (edge 44 · fused 17) ✓ report report_v1.pdf · objects.csv { "pipeline": "particle-size@2.4.1", "inputs": 38, "objects": 1842, "excluded": 61, "params": { "min_px": 4, "flatten": "plane" }, "stats": { "mean_nm": 31.4, "sd_nm": 9.7 }, "inputs_sha256": ["9f1c…", "a3d0…", …] }
The manifest is what makes a result checkable months later: input hashes, pipeline version, every parameter, every exclusion. Schematic values.
Why the numbers hold
Three things this buys you
Hand-measuring a few dozen objects gives you a picture. Measuring thousands, the same way every time, gives you a result.
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.
Scope
What we measure
DNA contour length and topology
Traced contour length per molecule, end-to-end distance, and topological class.
nm · per molecule
Protein binding position and occupancy
Where along the DNA each protein sits, and what fraction of molecules carry one.
position (bp / nm) · occupancy
Nucleosome wrapping
Wrapped length, opening angle and arm lengths for every nucleosome in the field.
bp wrapped · angle
Amyloid aggregate volume and morphology
Volume, height and elongation of oligomers and fibrils, with class-level statistics.
nm³ · aspect ratio
Particle size and heterogeneity
Size distributions for nanoparticles and vesicles, with subpopulation detection.
height · diameter · volume
A measurement that does not yet exist
Method development builds and validates a pipeline for your assay, with criteria agreed up front.
scoped individually
Engagement
From enquiry to delivered result
Two stages. The first exists so that the second can be quoted at a firm price. See the pricing sheet.
-
Step 01
Enquire
Tell us what you need measured and roughly what data you have. You get a reply saying whether it is feasible.
Free -
Step 02
Feasibility assessment
Send 10 to 20 representative images. We run the pipeline and report how many measurable objects your data contains, with a firm fixed price.
$500 · credited -
Step 03
Full analysis
Inputs are frozen on receipt. The pipeline runs with version and parameters recorded, and detections are reviewed against fixed QC criteria.
From $1,500 -
Step 04
Delivery
A versioned PDF report, the per-object CSV and the JSON run manifest, so any number traces back to a specific file.
Within one week
Filliaux Industries
Two products, one idea
Take the manual, unrepeatable steps out of getting from data to a figure.
01 · Service
Quantitative AFM Image Analysis
A measurement service. You send AFM images, you receive distributions, per-object data, and a record of the pipeline version and parameters that produced them.
For research groups, core facilities, contract laboratories, and industry programs that need numbers from images rather than representative pictures.
02 · Software
LabTools
A desktop platform for scientific data analysis, taking a dataset from plot to figure to manuscript in one place.
In active development. Free for academic and individual use.
Questions
Frequently asked questions
Who can analyse my AFM data?
Filliaux Industries runs automated measurement pipelines on atomic force microscopy images as a service. The analysis is done by Shaun Filliaux (PhD in biophysics, postdoctoral research in AFM and single-molecule biophysics), so you deal with the person doing the analysis.
What can be measured?
Validated pipelines exist for nucleosomes or chromatin on DNA, a protein bound to DNA, and amyloid-beta aggregates. DNA contour length, particle and vesicle size, and other samples are assessed individually, and method development builds a pipeline for a measurement that does not yet exist.
How much does AFM image analysis cost?
A feasibility assessment is $500 and is credited in full if you proceed. Academic project analysis starts from $1,500 (the minimum for every project), method development from $4,000, and training $1,200 per day. Commercial work is quoted after assessment. Prices are in USD and are starting points; the feasibility assessment produces a firm fixed price.
How long does it take?
Projects are delivered within one week of receiving the complete dataset. The clock starts on receipt of the complete dataset, not first contact, and pauses while awaiting decisions or clarification. Enquiries are usually answered within two to three working days, and always within one week.
What do I get back?
Three files: a versioned PDF report with figures, summary statistics and methods; a per-object CSV with every individual measurement; and a JSON run manifest with input file hashes, pipeline version, every parameter and every exclusion with its reason. One round of revisions is included.
Which file formats do you accept?
Raw instrument files. Bruker NanoScope, Asylum Research IBW, NT-MDT and Gwyddion (.gwy) are tested end to end; JPK, Park Systems and Nanosurf files are supported on request. Exported PNG or TIFF images cannot be measured because they have lost the height data.
How do I start?
Request a quote at data.filliaux.com/quote/ with one to ten representative raw images (up to 250 MB each), or email analysis@filliaux.com. The request is free and commits you to nothing; the reply says whether the measurement is feasible on your data and what it would cost.
Is my data kept confidential?
Client data is held in access-scoped storage and used for nothing but the engagement. Raw inputs are retained for 90 days after delivery and then removed. An NDA can be put in place before any data is sent.
Get started
Find out if it is possible on your data
A quote request costs nothing and tells you whether the measurement can be made. If it looks feasible, a feasibility assessment at $500 establishes how many measurable objects your data actually contains, and produces a firm fixed price.