Data for McGovern et al, 2024: Finding and Following: A deep learning-based pipeline for tracking platelets during thrombus formation in vivo and ex vivo

Data for McGovern et al, 2024: Finding and Following: A deep learning-based pipeline for tracking platelets during thrombus formation in vivo and ex vivoIn these directories you will find example data to run the software described in the paper:segmentationtraining_data: example frames (training_data/training_images) and corresponding ground truth segmentations (training_data/training_gt) that can be used to train the U-net described in the paper.{exvivo,invivo}_example: example images with multiple matching corresponding manual segmentations that can be used to validate the U-net's performance.tracking image datasets that can be segmented with the U-net trained from the segmentation data, then tracked and analysed.The data format is OME-NGFF v0.4, an emerging open format for bioimaging data and metadata. It can therefore be opened with open software in various ecosystems^[1]. To open the files in napari, install the napari-ome-zarr plugin and then (for example):<pre><pre>napari --plugin napari-ome-zarr tracking/mouse_invivo/200527_IVMTR73_Inj4_saline_exp3.ome.zarr<br></pre></pre>Note, however, that due to a current implementation issue with napari-ome-zarr, the opened segmentation files will not be manually editable with napari. For the moment, use the data loading widget from iterseg if you want to paint into the segmentation data.<br>https://ngff.openmicroscopy.org/tools/ ↩︎

McGovern等人2024年研究配套数据集：《定位与追踪：用于体内外血栓形成过程中血小板追踪的深度学习管线》

本目录下包含复现论文所述软件所需的示例数据：
- 分割训练数据集（segmentationtraining_data）：内含训练图像集（training_data/training_images）与对应的真值分割标注（training_data/training_gt），可用于训练论文中提及的U-net（U-Net）模型。
- {exvivo,invivo}_example：即体外（ex vivo）、体内（in vivo）示例数据集，包含多组匹配的手动分割标注图像，可用于验证U-net模型的性能。
- 追踪图像数据集：可使用由分割训练数据训练得到的U-net模型完成分割，随后进行追踪与分析。

本数据集采用OME-NGFF v0.4格式，这是一种新兴的生物成像数据与元数据开放标准格式，可通过多生态系统下的开源软件读取^[1]。若需在napari软件中打开此类文件，请先安装napari-ome-zarr插件，随后可参考如下示例命令：
<pre><pre>napari --plugin napari-ome-zarr tracking/mouse_invivo/200527_IVMTR73_Inj4_saline_exp3.ome.zarr<br></pre></pre>

但需注意：当前napari-ome-zarr插件存在实现缺陷，导致通过napari打开的分割文件无法进行手动编辑。若需对分割数据进行手绘修改，请暂时使用iterseg提供的数据加载组件。

参考链接：https://ngff.openmicroscopy.org/tools/ ↩︎