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Hosted by Zixiong Cao, Dragonfly application specialist at ORS. This lesson introduces users on How to render a volume in ORS Dragonfly imaging software. Download and Get Started with Dragonfly https://www.theobjects.com/dragonfly/... Watch the Playlist with all of the Dragonfly Daily tutorials on YouTube http://orss.ca/ytp2 Topics in this tutorial: 1-Starting from version 2020.1 Dragonfly has two rendering engines. -Make sure you use the “new engine” which provides superior quality. -Find the option for using the new rendering engine in Preferences 2-Working with LUT ( Look Up Table ) -3D Settings Menu -LUT presets -Editor Window to cutomize LUT 3-Working with Window Levelling -How Window Level determines which voxels are visible and wich are invisible. -Differences between the old and the new engine in applying LUT -Range of intensities and threshold. 4-Using Visual Shape to apply multiple LUTs to one volume 5-Export 3D Rendering as a high resolution picture with transparent background Acknowledgments: Demo data courtesy: Sanying Precision Instruments Co.Ltd Tianjin, China. Let's Connect 🡆 Twitter- / orsdragonfly3d 🡆 LinkedIn: / object-research-systems 🡆 ORS Website: ORS Website: https://www.theobjects.com 🡆 Sales-related inquiries: sales@theobjects.com 🡆 Support: support@theobjects.com About ORS Object Research Systems (ORS) develops deep learning powered 3D visualization and image analysis software. Dragonfly and Dragonfly Cloud, ORS’ flagship products, provide innovators from leading universities or industries, an advanced machine learning and neural networks based segmentation engine. Dragonfly's quantification tools then provide powerful options for counting, measuring, and characterizing image features, such as pores, fibers, grains, and much more. Its user-friendly experience translates its powerful and accurate quantitative findings in high-impact visuals. The ability to build fully automated workflows also enables reproducible results. #dragonfly #microscopy #deeplearning #imagesegmentation #microCT #FIBSEM #scientificimaging #electronmicroscopy #imageprocessing