Dragonfly Daily 08 ROI (region of interest) tools in Dragonfly (2020)

Hosted by Mike Marsh, Dragonfly Product Manager at ORS Download and Get Started with Dragonfly https://www.theobjects.com/dragonfly/... This is lesson 8 in an ongoing daily tutorial series that teaches new users how to become Dragonfly experts in no time. This lesson introduces users to ROI (region of interest) tools for image segmentation. Watch the Playlist with all of the Dragonfly Daily tutorials on YouTube http://orss.ca/ytp2 Topics in this tutorial • Basics ◦ New, Clear, Invert ◦ Undo • Range ◦ Adding and removing by manual thresholding ◦ Automatic thresholding • Coloring ROI ◦ Manually ◦ From template of colors • Clipping ◦ Adding, removing (thresholding-gate But before you get to far maybe you could d) ◦ Splitting an existing ROI (region of interest) into “foreground” and “background” • Creating a multiROI (multi region of interest) ◦ From material ROIs (regions of interest) ◦ By connected components indexing • Using an ROI to mask an image Acknowledgments: • 2D SEM of sandstone by Yufu Niu, UNSW (University of New South Wales, Sidney, Australia ) https://www.researchgate.net/profile/... https://www.researchgate.net/institut... • 3D FIBSEM of mouse retina rod internal segments by Christopher Bleck at NHLBI/NIH (National Heart, Lung, and Blood Institute) Bethesda, Maryland, USA https://www.nhlbi.nih.gov/science/ele... https://www.nhlbi.nih.gov/ Let's Connect 🡆 Twitter-   / orsdragonfly3d   🡆 LinkedIn:   / object-research-systems   🡆 ORS Website: ORS Website: https://www.theobjects.com 🡆 Sales-related inquiries: [email protected] 🡆 Support: [email protected] 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