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Automated Quality Control

We provide an AI-powered solution for automated quality control of digital histology slides in the pathology workflow.

 

Histological slides may show reduced interpretability because of variations in pre-analytical processes and scanning artifacts. High-quality and efficient workflows are essential to ensure effective and timely pathology diagnostics. AiosynQC automates and simplifies the quality control process.

AiosynQC analysis

Out-of-focus regions of an H&E stained slide image, blurry and difficult to read, are identified and highlighted with AiosynQC. The algorithm detects the most common artifacts in whole slide images.

Improve the quality of the diagnostic process

Improve the quality of the diagnostic process

AiosynQC helps labs ensure that only high-quality images are used by pathologists. The algorithm detects and highlights the most common artifacts in H&E and IHC slides.

Reduce time spent on Quality Control

Reduce time spent on Quality Control

Automating quality control increases the efficiency of the diagnostic and research workflow by reducing the amount of time spent on manual inspection of image quality.

Start working with AI algorithms

Start working with AI algorithms

Integrating AI-powered solutions will improve your digital pathology workflow. Automating QC will ease the use of other algorithms that underperform when artifacts are present.

Integrated in your workflow

Our automated quality control solution can be integrated with major workflow providers such as Sectra and Paige. Slides are prepared as usual, and the algorithm analyzes images once uploaded to the platform. AiosynQC offers tailored sensitivity and customizable reporting options, adapting to the unique needs of every laboratory.

Discover Aiosyn’s AI-Powered Algorithm for Image Quality Control

AiosynQC automatically recognizes and flags the most common artifacts to improve the quality and speed of digital pathology workflows. Tightly integrated in existing workflows, this application advances clinical diagnostics, prevents delays, and makes digitization of large cohorts much easier.

Schedule a demo for AiosynQC

Book a demo to discover how our automated QC works on your images and how it will help to further improve the digital pathology workflow.

Questions? We are happy to answer

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    The most frequent questions asked about AiosynQC

    • Is AiosynQC limited to hematoxylin and eosin (H&E) staining or it can assess immunohistochemistry (IHC) slides as well?

      AiosynQC supports both H&E and IHC staining.

    • Can AiosynQC be run on-premise?

      Yes, the software can be run on-premise as well as in the cloud. 

    • Does the tool only classify a slide image as having or not having artifacts, or does it also segment the area of the artifact?

      AiosynQC detects the most common quality artifacts and segments the affected areas. Additionally, the reporting and classification of slides as compromised or not can be adjusted to meet the specific needs of the laboratory. For example, labs can choose to flag only tissue folds larger than a specific area while not highlighting smaller tissue folds. 

    • What types of artifacts can the software detect?

      AiosynQC can detect the most common quality artifacts in whole slide images (WSIs), including out-of-focus areas, air bubbles, tissue folds, and pen markers.

    • What file types are compatible with AiosynQC?

      The tool is compatible with OpenSlide and supports various standard formats such as TIFF, SVS, MRXS, and more.

    • Is the software CE-marked?

      AiosynQC is not CE-marked because, under the European IVDR, it is not considered a medical device in the EU, nor is it intended to be used as an accessory to any AI or other medical devices.

    • What percentage of slides are flagged by AiosynQC?

      The incidence of artifacts varies depending on the laboratory workflow and equipment. AiosynQC offers tailored sensitivity and customized reporting options to adapt to the specific needs of each laboratory. For instance, labs may choose to flag images with significant anomalies while ignoring small artifacts that typically do not compromise readability. However, other centers may prefer a more comprehensive review to ensure all images sent to the pathologist are of high quality and do not require a rescan.