Cloud-based Karyotype analysis
Scanner agnostic karyotyping application
Explore expert content on scaning imaging and analysis.
Introducing automation into a pathology or cytology laboratory is not simply a matter of selecting a system with the right capabilities. The more important question is how that technology will function within your laboratory's actual workflow.
Automation can bring greater consistency, efficiency, and scalability to cytogenetics workflows—but successful automation starts long before a system is installed.
When you invite a technology provider into your laboratory for a workflow assessment, you should expect more than a standard product demonstration.
Laboratory bottlenecks are not always caused by a lack of equipment or processing capacity. In many cases, delays occur because highly trained professionals are spending time on tasks that could be streamlined through better software, workflow design, or IT infrastructure. Before investing in new technology, laboratories should identify exactly where time is being lost.
Detection, segmentation and classification are the three tasks behind most AI-assisted cell imaging. What each one does, what training data they need, and where expert review stays essential.
An algorithm does not look at a cell the way a pathologist does. It measures features. Understanding which features drive automated analysis explains both its usefulness and its limits.
Higher magnification makes an image bigger. It does not necessarily make it more detailed. The distinction matters when images are acquired for automated analysis.
When fluorophore spectra overlap, light from one probe can appear in another channel. What causes bleed-through, how it can affect interpretation, and the imaging factors that reduce it.
Once karyotype images are digital, analysis no longer has to happen beside the microscope. What a connected review workflow looks like, and what laboratories need to plan for.
Dashboards are easy to build and easy to misuse. What laboratory teams genuinely gain from visibility into case status, review queues and system activity, and where to be careful.
Immunofluorescence (IF) multiplex staining is a powerful technique that allows researchers to visualize multiple targets simultaneously in a single sample. This method provides detailed insights into cellular processes and interactions, making it an invaluable tool.
For over 25 years, BioView has been developing automated FISH imaging and analysis systems. Throughout the years, BioView has introduced new technological advancements to enhance both image quality and throughput while also reducing system maintenance and operating costs. LED fluorescent light sources allow us to do this. In this technical review, we share our insights on choosing the optimal fluorescent light source for your laboratory's needs.
Conventional workflows often divide the diagnostic question across multiple slides. Giemsa or another cytologic stain identifies cell type and morphology. Immunohistochemistry (IHC) or immunofluorescence identifies lineage or protein expression. FISH detects a deletion, amplification, translocation, or copy-number change.
Using a native hardened Tomcat server for remote access to clinical systems offers significant advantages over Citrix or Microsoft RDS. Tomcat minimizes attack surfaces, simplifies compliance, enhances security customization, and reduces resource consumption. Its browser-based access eliminates client-side software vulnerabilities, offering a cost-effective, secure, and high-performance solution tailored to clinical environments.
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