Data from: Segmentation of dense and multi-species bacterial colonies using models trained on synthetic microscopy images

This repository contains the relevant data and code for the article "Segmentation of dense and multi-species bacterial colonies using models trained on synthetic microscopy images" by Vincent Hickl, Abid Khan, René M. Rossi, Bruno F. B. Silva, and Katharina Maniura-Weber (arXiv version 3): Raw synthetic images of rod-shaped and circular cells Confocal microscopy images of densely packed colonies of Pseduomonas aeruginosa, and of mixed colonies of P. aeruginosa and Staphylococcus aureus Brigthfield microscopy images of rod-shaped and circular cells Synthetic images processed by cycleGAN, used as training data for segmentation models. A selection of trained segmentation models for dense Pseudomonas monolayers, and rod-shaped/circular cells in both confocal and brightfield microscopy images. The code for processing raw synthetic images using CycleGAN can be found at https://github.com/abid1214/cyclegan Further relevant code can be found at https://github.com/vhickl/synth-bacteria-segmentation, including code to: generate raw synthetic images of rod-shaped and spherical bacteria analyze orientational order in densely-packed colonies of rod-shaped cells quantitatively compare segmentation masks of bacterial colonies Please contact the authors ([e-mail]) if there are any issues or questions regarding this data.本仓库涵盖Vincent Hickl、Abid Khan、René M. Rossi、Bruno F. B. Silva以及Katharina Maniura-Weber所发表论文《基于合成显微图像训练模型的密集型多物种细菌菌落分割》（arXiv预印本第3版）的相关数据与代码： 杆状与圆形细菌细胞的原始合成图像 铜绿假单胞菌（Pseudomonas aeruginosa）密集菌落，以及铜绿假单胞菌与金黄色葡萄球菌（Staphylococcus aureus）混合菌落的共聚焦显微图像 杆状与圆形细菌细胞的明场显微图像 经循环生成对抗网络（CycleGAN）处理后的合成图像，用作分割模型的训练数据 针对密集型铜绿假单胞菌单层菌膜，以及共聚焦、明场显微图像中的杆状/圆形细菌细胞的多款已训练分割模型 用于通过CycleGAN处理原始合成图像的代码可在以下网址获取：https://github.com/abid1214/cyclegan 其余相关代码可在以下网址获取：https://github.com/vhickl/synth-bacteria-segmentation，其中包含以下功能代码： 生成杆状与球状细菌的原始合成图像 分析杆状细菌密集菌落的取向有序性 对细菌菌落的分割掩码进行定量比对 若对本数据集存在任何问题或疑问，请联系作者（[e-mail]）。