A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google's Colaboratory.

ABSTRACT: X-ray micro-computed tomography (X-ray μCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricu

SUBMITTER: Rippner DA 

PROVIDER: S-EPMC9514790 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature