Published April 2, 2021
| Version v1
Dataset
Open
Convolutional neural networks for segmentation of FIB-SEM nanotomography data from porous polymer films for controlled drug release
Authors/Creators
- 1. RISE Research Institutes of Sweden, Agriculture and Food
- 2. of Fibre and Polymer Technology, KTH Royal Institute of Technology
- 3. AstraZeneca
- 4. Department of Physics, Chalmers University of Technology
Description
Dataset and code used in F Skärberg, et al, "Convolutional neural networks for segmentation of FIB-SEM nanotomography data from porous polymer films for controlled drug release", published in Journal of Microscopy. In this work, we develop a segmentation method based on convolutional neural networks (CNNs) for focused ion beam scanning electron microscopy (FIB-SEM) data, acquired from porous polymer films made from ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. Herein, all codes in Python/Tensorflow and Matlab necessary to reproduce the results of the paper are supplied, together with the raw data, manual segmentations, trained models, and final segmentation results.