IMC Forum on demand video playlist

→ October 28, 2022 – Session I: Stepping Through the Pipeline: Recommendations and Considerations for In-Depth Analysis
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Get familiar with performing data visualization, data preparation, single-cell segmentation and single-cell analysis.

Learn about commonly used open source and commercial software algorithms and analytical tools and how our experienced FAS team can help you decide on an approach to meet your research goals.

Hear how analysis from a multi-omics approach including RNA sequencing and Imaging Mass Cytometry™ (IMC™) data was integrated to achieve key hepatocellular carcinoma insights.

→ June 15, 2022 - Igniting Insight into Immuno-Oncology
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Exploration of the tumor microenvironment (TME) is key to understanding the spatial relationships between cells and cell function in cancer pathology.

This IMC™ Forum started with a conversation about the impact of adding Imaging Mass Cytometry™ to the Lombardi Comprehensive Cancer Center at Georgetown University, which was followed by two presentations on research projects in hepatocellular carcinoma and colon cancer.

In the panel discussion, three expert researchers shared their experiences and insights, then took questions so attendees could learn more about the potential advantages of IMC powered by CyTOF® technology for their research.

→ April 25, 2022 - Current Methods and Future Views for Effective Cell Segmentation in High-Plex Imaging
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After an introduction by Fluidigm Chief Science Officer Andrew Quong, the event will include a presentation by Amy Bradshaw, PhD, Professor in the Division of Cardiology at the Medical University of South Carolina, and two panel discussions moderated by Hartland Jackson, PhD, Investigator at the Lunenfeld-Tanenbaum Research Institute.

The first panel discussion will feature hands-on experts addressing the current use of pipelines and offering up their tips, and the second will bring together three key thought leaders and expert algorithm developers to share their thoughts on the future of cell segmentation.

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