RooTrak: Automated Recovery of Three-Dimensional Plant Root Architecture in Soil from X-Ray Microcomputed Tomography Images Using Visual Tracking
RooTrak: Automated Recovery of Three-Dimensional Plant Root Architecture in Soil from X-Ray Microcomputed Tomography Images Using Visual Tracking
复制标题
DOI：
10.1104/pp.111.186221
复制
发表时间：
2012-02-01
期刊：
影响因子：
7.4
通讯作者：
Pridmore, Tony
中科院分区：
文献类型：
--
作者：
Mairhofer, Stefan;Zappala, Susan;Pridmore, Tony
X射线微计算机断层扫描（mu CT）是一种非常宝贵的工具，可以无创地可视化自然土壤环境中的植物根系。然而，根系材料的X射线衰减值的变化以及由水和有机材料引起的根系和土壤之间的衰减值的重叠是数据恢复的主要挑战。我们报告了自动根部分割方法和软件的开发，这些方法和软件将μ CT数据视为一系列图像，当x-y横截面沿着图像堆栈的z轴穿过时，根部对象似乎在其中移动。以前的方法采用了显着水平的用户交互和/或固定的标准来区分根和非根材料。RooTrak利用多个根外观的本地模型，每个模型在跟踪特定片段时构建，以识别新的根材料。它需要最少的用户交互，并能够适应不断变化的根密度估计。由于采用了视觉跟踪框架，对根材料的模型引导搜索使得RooTrak对X射线衰减数据的自然模糊性不太敏感。我们证明了RooTrak的实用性，使用mu CT扫描玉米（玉米），小麦（小麦），番茄（番茄）生长在一系列对比鲜明的土壤质地。我们的研究结果表明，RooTrak可以成功地从周围的土壤中提取一系列的根结构，并有望促进未来的根表型研究。
X-ray microcomputed tomography (mu CT) is an invaluable tool for visualizing plant root systems within their natural soil environment noninvasively. However, variations in the x-ray attenuation values of root material and the overlap in attenuation values between roots and soil caused by water and organic materials represent major challenges to data recovery. We report the development of automatic root segmentation methods and software that view mu CT data as a sequence of images through which root objects appear to move as the x-y cross sections are traversed along the z axis of the image stack. Previous approaches have employed significant levels of user interaction and/or fixed criteria to distinguish root and nonroot material. RooTrak exploits multiple, local models of root appearance, each built while tracking a specific segment, to identify new root material. It requires minimal user interaction and is able to adapt to changing root density estimates. The model-guided search for root material arising from the adoption of a visual-tracking framework makes RooTrak less sensitive to the natural ambiguity of x-ray attenuation data. We demonstrate the utility of RooTrak using mu CT scans of maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum) grown in a range of contrasting soil textures. Our results demonstrate that RooTrak can successfully extract a range of root architectures from the surrounding soil and promises to facilitate future root phenotyping efforts.