Presentation description

A key focus of cancer research is understanding how cells evolve in response to different drug treatments. Cancer's complexity and the vast amount of data generated by modern microscopy methods, such as Quantitative Phase Imaging, pose significant challenges for analysis. To address this, the Visualization Design Lab has been developing interactive visualization systems that provide both high-level overviews and detailed contextual information from microscopy images. Previous work by our lab has been published and received an honorable mention at IEEE VIS. However our lab's new revised tool named Aardvark shows even greater utility. The focus now is on creating cohesive visualizations that integrate cell images, time-series data, and tree data, moving beyond traditionally separating views of line charts, tree diagrams, and images. This approach aims to reduce the cognitive load on researchers by eliminating the need to mentally combine disparate data types. These design principles prioritize a primary data type as a layout while seamlessly incorporating other data types. Case studies have shown Aardvark's effectiveness in analysis, communication, and data cleansing for cancer cell microscopy data. By employing these new visualization design techniques, we aim to help researchers more effectively visualize, analyze, and handle the data related to cancer cell behavior in response to drugs.