Abraham Smith


Measured variables length, surface, diameter, count, segmentation
Operating system mac, windows, linux
Licence open-source
Automation level automated, semi-automated
Plant requirements any
Export formats png, csv
Other information

Scientific article(s)

RootPainter : Deep Learning Segmentation of Biological Images with Corrective Annotation
Abraham George Smith,Eusun Han,Jens Petersen,Niels Alvin Faircloth Olsen,Christian Giese,Miriam Athmann,Dorte Bodin Dresbøll,Kristian Thorup‐Kristensen
New Phytologist, 2022 View paper

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RootPainter is a GUI-based software tool for the rapid training of deep neural networks for use in biological image analysis. It is primarily used for the analysis of images of roots in soil and can handle complex and noisy images. RootPainter facilitates both fully-automatic and semi-automatic image segmentation. RootPainter uses a client server architecture and thus consists of a pair of programs (one on your computer, another on a server) that can, after an easy and user-friendly training process, identify and measure features in images. It is designed to be fully accessible to users without programming experience and has been tested with roots, root nodules, biopores and more recently trained to identify other kinds of features, such as leaves, inflorescences on canopy images and springtails in soil samples.

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