International research team led by Göttingen University develops user-friendly software method

Identifying and delineating cell structures in microscopy images is crucial for understanding the complex processes of life. This task is called “segmentation” and it enables a range of applications, such as analysing the reaction of cells to drug treatments, or comparing cell structures in different genotypes. It was already possible to carry out automatic segmentation of those biological structures but the dedicated methods only worked in specific conditions and adapting them to new conditions was costly. An international research team led by Göttingen University has now developed a method by retraining the existing AI-based software Segment Anything on over 17,000 microscopy images with over 2 million structures annotated by hand. Their new model is called Segment Anything for Microscopy and it can precisely segment images of tissues, cells and similar structures in a wide range of settings. To make it available to researchers and medical doctors, they have also created μSAM, a user-friendly software to “segment anything” in microscopy images. Their work was published in Nature Methods.

We are pleased to welcome Josh Moore (German BioImaging e.V. / Open Microscopy Environment Consortium) on January 23, 2025 at 2:15 PM in Goldschmidtstraße 1, Room 1.130. His lecture, entitled “Scalable strategies for a next-generation of FAIR bioimaging”, addresses the challenges facing the bioimaging community regarding increasingly large and complex image datasets. It also outlines strategies to implement the FAIR Data Principles (Findable, Accessible, Interoperable, Reusable) through cloud-native formats and effective metadata management.

Afterwards, there will be a get-together in Goldschmidtstraße 1, Room 2.143. We cordially invite everyone who is interested to join!

The Campus Institute Data Science (CIDAS) is looking to strengthen its team by hiring an IT staff member. You will be supporting the development and maintenance of central IT infrastructures as well as the further development of data science services. Are you interested in working in an interdisciplinary environment and shaping new technologies?

You can find further details about the position and information on the application process here:

Die Universitätsmedizin Göttingen (UMG) etabliert im CAIMed-Verbund eine Nachwuchsgruppe im Cluster „KI und Semantik“. Schwerpunkte sind die Entwicklung und Validierung von KI-Verfahren für die digitale Bilddiagnostik mit Blockchain-Technologien. Angesiedelt an der Professur für Digitale Pathologie, bietet die Position ein dynamisches, interdisziplinäres Umfeld für innovative Forschung.

Prof. Dr. Fabian Sinz, a member of the Campus-Institut Data Science (CIDAS), has been awarded an ERC Consolidator Grant for his “Vision2Action” project. Using a “digital twin” of the mouse brain, he investigates how movement influences the processing of visual stimuli. By applying innovative AI methods, the project seeks to provide novel insights into how motion and perception interact.