Dragonfly Daily 17 Image segmentation with Deep Learning in Dragonfly (2020)

Hosted by Mike Marsh, Dragonfly Product Manager at ORS
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This is lesson 17 in an ongoing daily tutorial series that teaches new users how to become Dragonfly experts in no time. This lesson introduces users to Image segmentation with Deep Learning in Dragonfly.

Watch the Playlist with all of the Dragonfly Daily tutorials on YouTube
http://orss.ca/ytp2

Topics in this tutorial
1-Mutiphase segmentation
-Denim fabric material. XRM from Rigaku.
-Small fibers, Big fibers, background

2-Single-phase segmentation
-HeLa cells. SEM from Zeiss. Courtesy of Cross Cancer Institute
-Mitochondria, Everything else as background

Publication reference in video: LORENZONI, RENATA et al . Semantic segmentation of the micro-structure of strain-hardening cement-based composites (SHCC) by applying deep learning on micro-computed tomography scans. CEMENT & CONCRETE COMPOSITES, v. 108, p. 103551, 2020.
http://dx.doi.org/10.1016/j.cemconcom...

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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 #deeplearning #TensorFlow #Keras #Denoising #SuperResolution #microscopy #imagesegmentation #microCT #FIBSEM #scientificimaging #electronmicroscopy #imageprocessing