The importance of pre-analytical processing

How to address variance in your samples


Do you face variability between digital slide images when performing your image analysis? 

In this webinar, Jeni Caldara will discuss common pre-analytical factors. Variance may increase the complexity of a dataset, which can negatively impact the quality and performance of image analysis algorithms. Numerous processes must occur to obtain, process, and digitize a sample, and each step can contribute to non-uniformity and sub-optimal image quality.  

Discover ways to overcome pre-processing variance in your samples: 

  • Developing artifact detection APPs
  • Training classifiers across dynamic sample
  • Normalization techniques within VIS

Join us for this series webinar to investigate the source of pre-analytical variables, their impact on subsequent analysis, and image analysis techniques to minimize variation. 

Ready to take your skills to the next level? Join our webinar and learn from the expert! 

Can't make it to this webinar? 
Don't worry, sign up anyway and we will send you the recording. 

Meet your speaker

Jeni Caldara
Professional Services Specialist 

Jeni Caldara is a Professional Services Specialists based in our Westminster, CO office. She graduated from Colorado State University with a Biological Science degree.  

Jeni came to Visiopharm with over 3 years of image analysis experience and started with us in August 2019. Jeni’s primary responsibilities include on-site and online training for new and existing customers, as well as helping them to become proficient with complex and creative APP development to derive contextual endpoints. 

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