DetecDiv Demo Project files

This demo project contains datasets that can be used to learn how to use the DetecDiv software. It contains : Raw microscopy images provided as individual .tiff files ( brightfield and fluorescence image series) Region of interests (ROIs) processed by DetecDiv to perform various classification tasks 3 different classification models that include all relevant information: Classifier definition parameters Training procedure parameters A trained classifier A formatted ground truth dataset ready to perform training An unformatted training and test set (ROIs) used to manually annotate images before training the classifier This demo project allows the user to test all the features of the graphical user interface of DetecDiv. For further details regarding the software and its applications, please refer to: DetecDiv, a deep-learning platform for automated cell division tracking and replicative lifespan analysis Théo Aspert, Didier Hentsch, Gilles Charvin https://doi.org/10.1101/2021.10.05.463175本演示项目包含可用于学习使用DetecDiv软件的配套数据集，具体内容如下： 1. 以单个.tiff文件形式存储的原始显微图像，涵盖明场与荧光图像序列； 2. 经DetecDiv处理的感兴趣区域（Region of Interests, ROIs），可用于执行各类分类任务； 3. 三种涵盖全部相关信息的分类模型，包含分类器定义参数、训练流程参数以及一个已训练完成的分类器； 4. 可直接用于模型训练的格式化真实标注（ground truth）数据集； 5. 未格式化的训练集与测试集（ROIs），用于在训练分类器前手动完成图像标注。 本演示项目可让用户完整测试DetecDiv图形用户界面的全部功能。如需了解该软件及其应用的更多细节，请参阅以下文献： DetecDiv：一款用于自动化细胞分裂追踪与复制寿命分析的深度学习平台 作者：Théo Aspert、Didier Hentsch、Gilles Charvin DOI：https://doi.org/10.1101/2021.10.05.463175