Title: DeepLineage

Duration: 2022 – 2025

Research Area: Life Science and Medicine

The project “DeepLineage” helps understanding how animals generate and regenerate cell diversity integrating live imaging, lineage tracking, deep learning and big image visualization.

Aims

We develop image analysis software for the exploration of cell-tracking data using unsupervised machine learning methods.

Problem

In-vivo fluorescence microscopy in the key technology for understanding how tissues form. Modern microscopes deliver staggering amounts of imaging data. Analysing this data is challenging, in particular when the data exceeds the capacity of local random access memory (RAM).

Technology

In this project, we contribute to the open-source project mastodon [1], a Fiji-plugin for tracking cells in big imaging data.

Outlook

Our contribution in the project “DeepLineage” will enable biologists to explore their data interactively using unsupervised machine learning techniques.

Publications

• https://github.com/mastodon-sc/mastodon-deep-lineage [1]

Team

Lead

• Dr. Robert Haase (Leipzig University)

Team Members

• Stefan Hahmann (TUD Dresden University of Technology)

Partners

• Michalis Averof (IGFL Lyon)
• Pavel Tomancak (MPI CBG Dresden)