Join Dr. Alexandra Lubin and Dr. Jason Otterstrom as they discuss the use of deep learning-powered automated microscopy and image analysis for fast, in vivo zebrafish screening.
To watch this webinar, please contact IDEA Bio-Medical: firstname.lastname@example.org.
Zebrafish are rapidly becoming a popular model organism for in vivo studies, particularly for drug screening and toxicology studies. Their benefits include fast development, economical husbandry, and direct amenability to microscopy since embryos are transparent. While imaging is fairly straightforward, in many cases, a substantial bottleneck to automated workflows is image analysis.
In this webinar, Dr. Jason Otterstrom and Dr. Alexandra Lubin describe an AI-powered analysis platform developed to enable true high-content screening of zebrafish, and highlight a range of applications where they have validated its performance. In brief, the easy-to-use software automatically identifies the fish outline, and internal anatomy & body regions with no required user inputs. They demonstrate the platform’s applicability in the context of counting GFP-labeled hematopoietic stem cells specifically in the tail region, along with measurement of x-ray induced apoptosis and dual-color analysis.
Key Topics Include:
- What is high-content imaging and how does it apply to Zebrafish
- How Deep-Learning can make analysis of zebrafish images truly high-content by extracting the fish’s anatomy
- Learn example assays where automated microscopy can facilitate use of zebrafish for screening studies
- One solution to orient zebrafish embryos without manual manipulation through specialized plates and software
Who Should Attend?
- Researchers using zebrafish and microscopy in their work
- Researchers looking for a model organism to do in vivo toxicology or drug screening
- People interested in automated screening of whole organisms
To retrieve a PDF copy of the presentation, click on the link below the slide player. From this page, click on the “Download” link to retrieve the file.
Post-Doctoral Research Associate
UCL Cancer Institute