Search

TrackMate is an automated tracking software used to analyze bioimages and distributed as a Fiji plugin. Here we introduce a new version of TrackMate rewritten to improve performance and usability, and integrating several popular machine and deep learning algorithms to improve versatility. We illustrate how these new components can be used to efficiently track objects from brightfield and fluorescence microscopy images across a wide range of bio-imaging experiments.

Modern life science relies heavily on fluorescent microscopy and subsequent quantitative bio-image analysis. The current rise of graphics processing units (GPUs) in the context of image processing enables batch processing large amounts of image data at unprecedented speed. In order to facilitate adoption of this technology in daily practice, we present an expert system based on the GPU-accelerated image processing library CLIJ: The CLIJ-assistant keeps track of which operations formed an image and suggests subsequent operations. It enables new ways of interaction with image data and image processing operations because its underlying GPU-accelerated image data flow graphs (IDFGs) allow changes to parameters of early processing steps and instantaneous visualization of their final results. Operations, their parameters and connections in the IDFG are stored at any point in time enabling the CLIJ-assistant to offer an undo-function for virtually unlimited rewinding parameter changes. Furthermore, to improve reproducibility of image data analysis workflows and interoperability with established image analysis platforms, the CLIJ-assistant can generate code from IDFGs in programming languages such as ImageJ Macro, Java, Jython, JavaScipt, Groovy, Python and C++ for later use in ImageJ, Fiji, Icy, Matlab, QuPath, Jupyter Notebooks and Napari. We demonstrate the CLIJ-assistant for processing image data in multiple scenarios to highlight its general applicability. The CLIJ-assistant is open source and available online: https://clij.github.io/assistant/

A new Floating Sub-Structure concept has been developed for Floating Offshore Wind Turbine (FOWT). It consists of a floating tubular sub-structure connected with tendons to a counterweight providing pendulum-restoring forces. The whole floating system is anchored with six low-tension mooring lines. Model tests were carried out in wave basin test facilities at Ecole Centrale de Nantes to provide insight into hydrodynamic behavior of the system under operational and extreme wave conditions. Two installation depths were studied: intermediate and deeper water depth configurations with 75 and 150 meters water depth respectively. Two wind turbine capacities were tested: 8MW and 12MW. Responses of the system were investigated under different irregular wave conditions: operational condition with significant wave height Hs = 4 m and two extreme wave conditions with significant wave heights Hs=8m and 14 m. Sensitivity tests were also performed for various wave periods Tp (Tp = 8, 12 and 16 seconds). Results of these tests demonstrate that the floater is extremely stable with very low pitch motions as well as low vertical & horizontal accelerations both in operational and extreme wave conditions. Detailed results are presented in this paper. This stable dynamic behavior is obtained because natural periods of the floater are far away from wave spectrum peak and it thus leads to low dynamic loads in the mooring lines. This beneficial seakeeping feature and the possibility of accommodating even larger wind turbines with minor modifications on the floater design make the proposed FOWT a relevant concept for the upcoming offshore floating wind market.