Aiosyn expands AI-powered quality control with incomplete scan detection
Nijmegen, the Netherlands – Aiosyn, a pioneering innovator in AI-powered pathology software for cancer and kidney disease, has introduced a new enhancement to its automated quality control (QC) solution, AiosynQC. The latest update enables the detection of incomplete slide scanning, where parts of the tissue are missing in the whole-slide image due to scanning errors.
AiosynQC recognizes and segments common artifacts in hematoxylin and eosin (H&E) and immunohistochemistry (IHC) digital slides, flagging affected images for recutting or rescanning before they reach a pathologist. With this new feature, laboratories can automatically identify incomplete scans, reducing the need for manual review and allowing technicians to rescan affected samples more efficiently.
In digital pathology, scanned slides must accurately represent the original glass slides. However, scanners sometimes fail to capture certain tissue areas, leaving blank regions in the digital image. This issue commonly occurs in samples with large amounts of fatty tissue, such as breast biopsies, where low contrast can cause scanners to miss part of the tissue. While some missing areas may not impact diagnosis, in other cases, critical regions could be left out, requiring a rescan with adjusted focus points. AiosynQC can now automatically detect these scanning errors, helping laboratories ensure higher-quality digital slides and minimizing workflow disruptions.
“Incomplete scans can compromise diagnostic accuracy and cause delays. With this enhancement to AiosynQC, we are helping pathology laboratories streamline quality control, reduce manual workload, and ensure that only complete, high-quality digital slides are used in diagnostics and research.”Patrick de Boer, CEO of Aiosyn
AiosynQC is a modular, flexible solution designed to integrate seamlessly with existing digital pathology systems. Available for both on-premise and cloud deployment, it provides laboratories with automated slide quality control that fits right into their pre-analytical processes. The addition of incomplete scan detection reinforces Aiosyn’s commitment to improving digital pathology workflows and ensuring high-quality slides for manual or AI-powered analysis.
To explore AiosynQC and test the algorithm on your whole–slide images, contact Aiosyn at contact@aiosyn.com.
Figure 1. AiosynQC identifies and highlights incomplete scans. The left image shows a whole-slide image with missing tissue areas. The right image illustrates the algorithm detection, including tissue (green) and regions with incomplete scanning (red).
About Aiosyn
Based in the Netherlands, Aiosyn develops precision pathology software for breast cancer and kidney disease, integrating its solutions into standard pathology workflows. Aiosyn has been built upon more than 20 years of research experience in the field of pathology and is rooted in pathology practice.
AiosynQC
AiosynQC is not a medical device under the EU IVDR and the UK MDR 2002. It is not intended to be used as an accessory to, nor is it necessary to be used in combination with, any AI or other medical devices to specifically enable them to meet their intended purpose or directly assist in their functionality. AiosynQC is for Research Use Only (RUO) in the United States or any other jurisdiction.
SOURCE: Aiosyn
