The practice of histopathology faces several challenges; specifically an increasing number of cases that must be processed and diagnosed faster while reducing cost. At the same time pathologists and scientists are challenged, especially on data quality, by competing diagnostic modalities such as gene expression assays.
In order for histopathology to stay competitive and relevant, the quality of diagnostic data generated must improve while reducing costs and improving turnaround times. Recent research has identified automated, robust and reliable tumor cell detection as a pivotal tool both for improving of data quality and for enabling automation. This webinar will present new technology, methods, and workflows that have the potential to achieve these important goals.