Convolutional neural networks for segmentation of FIB-SEM nanotomography data from porous polymer films for controlled drug release

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.本数据集及代码对应F Skärberg等人发表于《显微学杂志》(Journal of Microscopy)的论文《用于控释药物多孔聚合物薄膜FIB-SEM纳米断层扫描数据分割的卷积神经网络》("Convolutional neural networks for segmentation of FIB-SEM nanotomography data from porous polymer films for controlled drug release")。该研究开发了一种基于卷积神经网络（Convolutional Neural Networks, CNNs）的图像分割方法，用于处理由乙基纤维素（Ethyl Cellulose, EC）与羟丙基纤维素（Hydroxypropyl Cellulose, HPC）聚合物共混物制备的多孔聚合物薄膜的聚焦离子束扫描电子显微镜（Focused Ion Beam Scanning Electron Microscopy, FIB-SEM）纳米断层扫描数据。本数据集提供了可复现该论文研究结果所需的全部Python/TensorFlow及Matlab代码，同时附带原始数据、人工分割标注、训练完成的模型以及最终分割结果。