Thus biologists increasingly rely on computer scientists to come up with new solutions and on software to apply those solutions. In recent years, with the adoption of automated microscopy technologies, the volume and complexity of image data has increased to the point that it is no longer feasible to extract information without employing computers. Much primary biological data is acquired as images. The nuclei are colored according to the angle in which they were detected. The video shows a result of segmentation and tracking algorithm that follows the movements of cells through the gastrulation process. Cellular blastoderm stage Drosophila embryo expressing His-YFP marker in all cells has been imaged from five angles using SPIM throughout gastrulation. Segmentation and tracking of nuclei in Drosophila embryo. The displacement at each iteration averaged across all descriptors is shown in lover left corner. The nuclei of the embryo specimen are shown in grey. The bead descriptors (representing constellations of sub-resolution fluorescent beads added to the rigid agarose medium in which the embryo was mounted) are colored according to their displacement at each iteration of the optimizer (red - maximum displacement, green – minimum displacement). ![]() The video visualizes the global optimization that is using local geometric bead descriptor matches to recover the shape of the embryo specimen. Drosophila embryo expressing His-YFP marker has been imaged in a spinning disc confocal microscope from 18 different angles improvising rotation using custom made sample chamber. Visualization of bead-based registration of multi-view microscopy scan of Drosophila embryo. The number in the upper right corner indicates the section index. The lateral resolution of the raw data is 4 nm/pixel. melanogaster first instar larval ventral nerve cord at four different zoom levels (A–D where B shows the close up of the blue rectangled area in A etc.). The movie shows in each frame a single section from the rigidly aligned TEM section series, imaged as mosaic of overlapping tiles, of the D. Walk through reconstructed large ssTEM mosaic of third instar larval ventral nerve cord. In order to emphasize the visualization effect all tiles within section are initially placed at the same location discarding their known configuration within section. The global optimization proceeds section by section and at each step distributes the registration error equally across the increasing set of tiles. The corresponding SIFT features that connect images within section and across section are shown as green dots, the residual error of their displacement at a given iteration of the global optimizer is shown as cyan line (iteration number and minimal, average and maximal error are shown in lower left corner). The video visualizes the process of reconstruction of such large section series on seven exemplary sections. The ventral nerve cord of Drosophila first instar larva was sectioned and imaged in electron microscope as a series of overlapping image tiles. Visualization of SIFT mediated stitching of large ssTEM mosaics. ![]() Between 23 rd of March to the 3 rd of April there was a Fiji hackathon in Dresden marked by increased developer activity that carries over the period after the hackathon ended – the so called “hackathon effect”. ![]() The class hierarchy is visualized as a dynamic tree, the developers are flying pawns that extend rays to classes which they newly created or into which they introduced changes. The video produced using gource tool in Git visualizes the changes to Fiji source code repository from March 15 th 2009 until May 16 th 2009. The future of Fiji as application layer of ImageJ2 An estimate of Fiji users based on wiki traffic I also simplified the CompositeProjection switch logic, removing the part concerning the is("Inverting LUT") property, as it doesn’t seem to be necessary now.NIHMSID 517436 Supplement: Supplementary Figure 1. I modified the original script to accomplish this: I put together a couple of helper functions to do these color space conversions for a given triplet (*), and applied the same algorithm to each LUT. Then it hit me: the same can be done for LUTs! The algorithm behind this tool relies on inverting the image, converting form RGB to HSB (HSV) space, rotating hues 180°, and converting back to RGB again. It also features a final gamma correction, but can be disabled (or customized) via right click: Just to add to this topic, and for future reference: as part of the twitter thread that sparked this color inversion theme revival, (or ?) and I ended up putting together an action tool macro to exactly accomplish this very same approach invertion, but using a faster alternative than the pixel-by-pixel macro call: Invert RGB image without changing colors Image Analysis
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