AI-based automatic analysis of mouse behavior in videos
Understanding and minimizing itching is a critical aspect of developing medical treatments, yet there’s no standardized method to measure it effectively. At DKFZ, researchers use a specialized setup where mice are injected with different chemical compounds that trigger itching. Videos are recorded to observe how often and how long the mice scratch specific areas, providing valuable insights into itch quality and ultimately into itch signaling mechanisms. However, manually analyzing these videos is a slow and labor-intensive process.
To optimize this workflow, we are creating an AI-based video analysis tool. Our classifier automatically identifies and tracks the mouse’s behavior frame by frame, providing precise measurements of scratching activity. This innovation accelerates the analysis process, enabling researchers to process more data in less time and advance medical research in this critical area.
Other Collaborations
Automated Analysis of Evolutionary Experiments of Phytoplankton
There is a strong interest in understanding community assembly and dynamics. Experimental approaches using phytoplankton have proven to be extremely insightful to unravel underlying biological processes. Imaging flow cytometry is an emerging method becoming more and more popular in different fields. It allows us to capture changes within a community or population in a more […]
BetaSeg
Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and spatial analysis is necessary. Here we describe a practical and annotation-efficient pipeline for organelle-specific segmentation, spatial analysis and […]