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This webinar will address a different approach to Image Analysis Verification, with a focus on the entire process to include slide preparation, scanning and analysis. Traditionally, Anatomic Pathology Laboratories have evaluated the accuracy of image analysis results by comparing the end point of the process, or the results of the image analysis algorithm, to other test methods and results from other laboratories.
The approach discussed during this webinar will focus in on the entire process. The first step in grasping the importance of this concept is understanding that the results of a standardized histology process can vary. So it is important to understand the sources of variation, the degree of variation and the impact of that variation on the image analysis algorithm. Procedures can be developed and tested to determine how variation in the histology and scanning process can affect image analysis results. This process will help determine and document the robustness of an image analysis algorithm so that the data or results generated are accurate and reproducible.
- Define basic terminology.
- Discuss the sources, degree and impact of variation within the histology process on the robustness and accuracy of an image analysis algorithm.
- Demonstrate how to write and execute a verification protocol that can evaluate the entire histology, scanning and analysis process to include accuracy, precision and repeatability.
LAURALEE MCMAHON: Thank you it is my pleasure to be here and thank you, Leica, for sponsoring this. I am happy to be here and thank you to everyone for taking time out of their busy day to join me.
Just a little bit of a brief background of myself. I have been a histo-technologist for 15, going on 16, years and a supervisor of the immunohistochemistry lab here at the University of Rochester for about 8 years. Our lab performs general IHC for clinical use using automated equipment. We also do