Speaker: Eric Mörth (Harvard Medical School)
Technological advances in biological experimental approaches for studying human tissues at single-cell resolution are producing large amounts of complex data and are offering new ways to ask questions with far-reaching impacts on human health. To allow for comprehensive analysis and comparison of the generated data, the ultimate goal is to construct an atlas of the human body that characterizes the cell types, tissue structures, and abundance of different types of biomolecules across these structures. The data supporting these atlas efforts, however, is creating challenging visualization problems due to 1) the dimensionality and density of the data and 2) the multi-modal measurements (including proteins, genes, and metabolites) associated with these structures in both 2D images and 3D volumes. Additionally, many datasets routinely include tens of thousands to millions of cells, with up to thousands of measurements per cell, resulting in critical scalability challenges. This new paradigm of tissue atlas construction presents many relevant visualization challenges that will require the visualization community’s expertise to address. Due to the inherent anatomical nature of the data, biologists need to interact with this data in spatial and hierarchical contexts using visualization systems that are able to handle multi-modal visualization and queries at scale. In this talk I will reflect on the outcomes of our Application Spotlight sessions at IEEE VIS 2023 in Melbourne Australia.
Speaker BIO: Eric Moerth is a Research Fellow (PostDoc) in Biomedical Informatics at Harvard Medical School. He received his PhD from the University of Bergen in Norway, under the supervision of Prof. Noeska Smit. During his PhD study, Eric Moerth conducted research in multimodal medical visualization. His main focus was the research of new and innovative ways to visualize and explore medical data, e.g. MRI data to enable doctors to have a better view at their data. His projects resulted in successful publications in the field of medical visualization.
