Projects
With our Helmholtz Imaging Projects, Helmholtz Foundation Model Initiative (HFMI) and third-party funded projects, we aim to initiate cross-cutting research collaborations and identify innovative research topics in the field of imaging and data science.
Helmholtz Imaging offers a funding line of Helmholtz Imaging Projects, striving to seed collaborations between centers and across research fields. They are a strong incentive to enable interdisciplinary collaboration across the Helmholtz Association and an incubator and accelerator of the Helmholtz Imaging network.
In addition to our Helmholtz Imaging Projects, the Helmholtz Imaging team has secured external funding for third-party projects contributing their knowledge and expertise on cutting-edge imaging methodology.
Join us in unlocking the limitless potential of Helmholtz Imaging!
The next call for Helmholtz Imaging Projects is OPEN until July 30, 2025. Find out more about the project call in this summary.
Helmholtz Imaging Projects
WeMonitor
Satellite-based Earth observation to detect natural hazards
Satellite imagery makes it possible to detect spatio-temporal anomalies on the Earth's surface, including natural hazards such as landslides, deforestation, or the emergence of large waste dump sites. This project aims to use artificial intelligence to detect these changes at an early stage and to be able to monitor their progress.
DIPLO
Paving the way from in situ plankton image data to a Digital Twin Ocean
This project will develop a user-friendly software platform to analyze plankton images independent of the instrument with which images were collected. This will help to compare data and create a common database, which is a critical step towards an image-based ecosystem component of a “Digital Twin Ocean”.
CLARITY
CineMR-guided ML-driven Breathing Models for Adaptive Radiotherapy
Dose-escalated radiotherapy of lung cancers requires precise monitoring of lesions and nearby organs at risk. Current methods are able to track ultra-central lesions but neglect their deforming vicinity, risking unacceptable toxicity to aortico-pulmonary structures. AI-based anomaly detection and generative AI models can address both requirements in real-time.Helmholtz Foundation Model Initiative (HFMI) Projects
Synergy Unit
The Synergy Unit amplifies the Helmholtz Foundation Model Initiative's impact by developing AI principles for diverse fields. Collaborating with HFMI projects, it focuses on knowledge sharing, community building, and representation to ensure the initiative's lasting influence.
The Human Radiome Project (THRP)
The Human Radiome Project (THRP) aims to drive a paradigm shift in medical research, providing novel insights into human health and disease through the power of AI. By integrating diverse radiological data, it seeks to enable groundbreaking advancements in personalized medicine, enhancing diagnostic accuracy and improving patient care.
AqQua
AqQua aims to build the first foundational pelagic imaging model using billions of aquatic images worldwide. These images, spanning species from plankton, will help an AI classify species, extract traits, and estimate carbon content, offering key insights into biodiversity, ecosystem health, and the biological carbon pump's role in climate regulation.Third-Party Projects
BestMeta
Behavioral Standard Metadata
Developing metadata standards and FAIR analysis pipelines for Video Tracking Assays (VTAs) in toxicology and medical sciences
Bayesian Computations for Large-scale (Nonlinear) Inverse Problems in Imaging
During research stays with the collaborating group at Caltech, we aim to investigate various aspects of statistical inverse problems. This includes inquiries into particle- and PDE-based sampling methods, as well as robust regularization using neural networks.