Sample, test, and validation data for findmycells

findmycells is an open source python package, developed to foster the use of deep-learning based python tools for bioimage analysis, specifically for researchers with limited python coding experience. It is developed and maintained in the following GitHub repository: https://github.com/Defense-Circuits-Lab/findmycells <strong>Disclaimer: All data (including the model ensemble) uploaded here serve solely as a test dataset for findmycells and are not intended for any other purposes.</strong> For instance, the group, subgroup, or subject IDs don´t refer to the actual experimental conditions. Likewise, also the included ROI-files were only created to allow the testing of findmycells and may not live up to scientific standards. Furthermore, the image data represents a subset of a dataset that is already published here: Segebarth, Dennis et al. (2020), Data from: On the objectivity, reliability, and validity of deep learning enabled bioimage analyses, Dryad, Dataset, https://doi.org/10.5061/dryad.4b8gtht9d The model ensemble (cfos_ensemble.zip) was trained using deepflash2 (v 0.1.7) Griebel, M., Segebarth, D., Stein, N., Schukraft, N., Tovote, P., Blum, R., &amp; Flath, C. M. (2021). Deep-learning in the bioimaging wild: Handling ambiguous data with deepflash2. <em>arXiv preprint arXiv:2111.06693</em>. The training was performed on a subset of the "lab-wue1" training dataset, using only the 27 images with IDs 0000 - 0099 (cfos_training_images.zip) and the corresponding est. GT masks (cfos_training_masks.zip). The images used in "cfos_fmc_test_project.zip" for the actual testing of findmycells are the images with the IDs 0100, 0106, 0149, and 0152 of the aforementioned "lab-wue1" training dataset. They were randomly distributed to the made-up subject folders and renamed to "dentate_gyrus_01" or "dentate_gyrus_02".findmycells是一款开源Python软件包，旨在推广基于深度学习的Python工具在生物图像分析中的应用，尤其面向Python编程经验有限的研究人员。该工具由以下GitHub仓库开发并维护：https://github.com/Defense-Circuits-Lab/findmycells <strong>免责声明：本仓库上传的所有数据（含集成模型（model ensemble））仅作为findmycells的测试数据集使用，不得用于其他任何用途。</strong> 例如，分组、子分组及受试者ID均不指代真实实验条件。同理，所包含的感兴趣区域（Region of Interest，ROI）文件仅用于测试findmycells，可能未达到科学研究标准。此外，本图像数据为某一已发表数据集的子集：Segebarth, Dennis 等（2020），数据来源：《论深度学习辅助生物图像分析的客观性、可靠性与有效性》，Dryad数据集，https://doi.org/10.5061/dryad.4b8gtht9d。该集成模型（cfos_ensemble.zip）基于deepflash2（v0.1.7）训练得到：Griebel, M.、Segebarth, D.、Stein, N.、Schukraft, N.、Tovote, P.、Blum, R. 与 Flath, C. M.（2021），《生物成像领域的深度学习：使用deepflash2处理模糊数据》，<em>arXiv预印本 arXiv:2111.06693</em>。训练过程使用了"lab-wue1"训练数据集的子集，仅选取ID为0000至0099的27张图像（cfos_training_images.zip）及其对应的真值掩码（cfos_training_masks.zip）。用于实际测试findmycells的"cfos_fmc_test_project.zip"中的图像，取自上述"lab-wue1"训练数据集中ID为0100、0106、0149及0152的图像。这些图像被随机分配至虚构的受试者文件夹中，并重命名为"dentate_gyrus_01"或"dentate_gyrus_02"。