de Reuille Pierre Barbier, Ragni Laura
University of Bern, Altenbergrain 21, 3013, Bern, Switzerland.
Center for Plant Molecular Biology-ZMBP, Developmental Genetics, University of Tübingen, Auf der Morgenstelle 32, 72076, Tübingen, Germany.
Methods Mol Biol. 2017;1544:103-125. doi: 10.1007/978-1-4939-6722-3_10.
Quantification of vascular morphodynamics during secondary growth has been hampered by the scale of the process. Even in the tiny model plant Arabidopsis thaliana, the xylem can include more than 2000 cells in a single cross section, rendering manual counting impractical. Moreover, due to its deep location, xylem is an inaccessible tissue, limiting live imaging. A novel method to visualize and measure secondary growth progression has been proposed: "the Quantitative Histology" approach. This method is based on a detailed anatomical atlas, and image segmentation coupled with machine learning to automatically extract cell shapes and identify cell type. Here we present a new version of this approach, with a user-friendly interface implemented in the open source software LithoGraphX.
次生生长过程中血管形态动力学的量化一直受到该过程规模的阻碍。即使在微小的模式植物拟南芥中，木质部在单个横截面上也可能包含2000多个细胞，使得手动计数不切实际。此外，由于其位置较深，木质部是难以触及的组织，限制了实时成像。一种可视化和测量次生生长进程的新方法已被提出：“定量组织学”方法。该方法基于详细的解剖图谱，以及图像分割与机器学习相结合，以自动提取细胞形状并识别细胞类型。在这里，我们展示了该方法的新版本，在开源软件LithoGraphX中实现了用户友好的界面。
