How To Overcome Challenges In Image Analysis For Spatial Biology w/ Lorenz Rognoni, Ultivue
Digital Pathology Podcast
English - June 08, 2023 14:00 - 20 minutes - 14.4 MB - ★★★★★ - 5 ratingsNatural Sciences Science Technology pathology digital image analysis medicine artificial intelligence pharma pharmaceutical healthcare Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Exploring Spatial Biology and Image Analysis with Lorenz Rognoni
Get ready for a deep dive into spatial biology and image analysis with Lorenz Rognoni, the Director of Image Data Science at Ultivue. Ultivue is a company specializing in spatial biology and Lorenz brings his wealth of knowledge in multiplex immunofluorescence (mIF) and image data science to this great conversation.
Multiplex IF: Challenges and Complexities
We kick off our discussion by addressing the inherent challenges in multiplex IF. The conversation spans a range of issues including tissue preparation artifacts, unique tissue morphology, and antibody-specific staining. The vast variability of tissues, differing across body regions, species, and health conditions, is a recurring theme. We also delve into the effectiveness of expert visual evaluation for traditional stains and the need for new strategies to interpret high-dimensional data.
Brightfield Imaging in Spatial Biology: Does it Still Play a Role?
Shifting gears, we discuss the role of brightfield imaging in spatial biology. Is there still space for brightfield if we want to learn the spatial interactions of cells in the tissue? Is this method not too limiting?
Lorenz underscores its continued relevance, particularly when robustness and scalability are prerequisites. He suggests transitioning to simpler methods like singleplex IF or even brightfield imaging, once research zeroes in on specific biomarkers of relevance with multiplex IF.
Transitioning from Image Analysis to Data Interpretation: Navigating the Pitfalls
Our conversation culminates in a look at the challenges and potential missteps in moving from image analysis to interpreting the data generated. Lorenz points out the crucial process of extracting meaningful insights from millions of cells, defining appropriate phenotypes, and considering the intricacies of downstream data mining.
Key Takeaways
Join us for this insightful conversation and gain a deeper understanding of the complexities and nuances of spatial biology and image data science with Lorenz Rognoni.
Keywords: Lorenz Rognoni, Ultivue, spatial biology, image analysis, multiplex immunofluorescence, tissue morphology, brightfield imaging, data mining
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