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Aiosyn

Digital slide quality assessments,no integration required

Artifacts and missed tissue areas introduced in preparation and scanning are rarely visible at the scale a batch is reviewed. Upload whole-slide images to the Aiosyn platform and the analysis runs outside your systems, with no connection to your image management system and nothing installed in the laboratory.

In the EU and the UK, AiosynQC is not a medical device under IVDR and UK MDR 2002. Research Use Only in the United States.

Request an assessmentAiosynQC in the laboratory
  • Secure upload
  • H&E, IHC, and other special stains
  • One-off or at your own interval
A batch of whole-slide images shown as thumbnails at low magnification, with the images AiosynQC flagged circled: a pen marker, a fold and heavily stained sections among several hundred clean ones.
Part of one assessed batch. The circled images are the ones the algorithm flagged.

From uploaded batch to assessment report

You upload the batch. The algorithm analyzes every image at pixel level and segments the regions it flags. The assessment comes back as a report, with each image openable in the viewer.

Whole-slide images are uploaded to the Aiosyn platform without full integration, AiosynQC performs an automated quality inspection, and a digital slide quality assessment report is returned.

Assessments run one-off, before an accreditation audit or after a change of scanner, or at a fixed interval where the record matters more than the single batch.

The assessment arrives as a report

Quantified per class and per image, so the batch can be judged as a whole and the images that need a new preparation or a rescan are named.

  • Artifact prevalence across the batch, per class
  • Share of tissue area affected, per class and per image
  • One row per image, linking into the viewer
  • Comparison against your own earlier assessments

Aiosyn publishes no full example report. We walk through a recent one on a call.

Two charts and a table from an assessment report: the number of whole-slide images carrying each artifact type, the share of tissue area affected per artifact type, and one row per image with its dominant artifact and its per-class area shares.
Artifact prevalence, affected tissue area and the per-image table, from an example assessment report.

The classes AiosynQC segments

The assessment runs the algorithm laboratories run in production, at the sensitivity set for your batch.

  • Out-of-focus areas
  • Incomplete scanning
  • Air bubbles
  • Tissue folds
  • Pen markers
  • Dust
  • White balance problems
  • Ink

Support for ISO 15189 and ISO 17025 accreditation

Artifact prevalence measured the same way on every batch is quantified evidence for a quality system, and it points staff training at the classes that dominate rather than at the ones that are easiest to see.

Also in the clinical track

Clinical overview

Send us a batch

Upload a set of whole-slide images and we will return the assessment of it, with nothing to install and nothing to connect.

Request an assessment