NODeJ: an ImageJ plugin for 3D segmentation of nuclear objects.

Tristan DubosAxel PouletGeoffrey ThomsonEmilie PéryFrédéric ChausseChristophe TatoutSophie DessetJosien C van WolfswinkelYannick Jacob

Published in: BMC bioinformatics (2022)

NODeJ allows for efficient automated analysis of subnuclear structures by avoiding the semi-automated steps, resulting in reduced processing time and analytical bias. NODeJ is written in Java and provided as an ImageJ plugin with a command line option to perform more high-throughput analyses. NODeJ can be downloaded from https://gitlab.com/axpoulet/image2danalysis/-/releases with source code, documentation and further information avaliable at https://gitlab.com/axpoulet/image2danalysis . The images used in this study are publicly available at https://www.brookes.ac.uk/indepth/images/ and https://doi.org/10.15454/1HSOIE .

Keyphrases

deep learning
convolutional neural network
high throughput
machine learning
high resolution
electronic health record
healthcare
single cell
cross sectional
optical coherence tomography