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首页> 外文期刊>Plant methods >Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography
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Recovering complete plant root system architectures from soil via X-ray μ-Computed Tomography

机译:通过X射线μ计算机断层扫描从土壤中恢复完整的植物根系体系结构

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Background X-ray micro-Computed Tomography (μCT) offers the ability to visualise the three-dimensional structure of plant roots growing in their natural environment – soil. Recovery of root architecture descriptions from X-ray CT data is, however, challenging. The X-ray attenuation values of roots and soil overlap, and the attenuation values of root material vary. Any successful root identification method must both explicitly target root material and be able to adapt to local changes in root properties. RooTrak meets these requirements by combining the level set method with a visual tracking framework and has been shown to be capable of segmenting a variety of plant roots from soil in X-ray μCT images. The approach provides high quality root descriptions, but tracks root systems top to bottom and so omits upward-growing (plagiotropic) branches. Results We present an extension to RooTrak which allows it to extract plagiotropic roots. An additional backward-looking step revisits the previous image, marking possible upward-growing roots. These are then tracked, leading to efficient and more complete recovery of the root system. Results show clear improvement in root extraction, without which key architectural traits would be underestimated. Conclusions The visual tracking framework adopted in RooTrak provides the focus and flexibility needed to separate roots from soil in X-ray CT imagery and can be extended to detect plagiotropic roots. The extended software tool produces more complete descriptions of plant root structure and supports more accurate computation of architectural traits.
机译:背景技术X射线微计算机断层扫描(μCT)能够可视化自然环境中生长的植物根-土壤的三维结构。但是,从X射线CT数据中恢复根体系结构描述具有挑战性。根和土壤的X射线衰减值重叠,并且根物质的衰减值变化。任何成功的根部识别方法都必须明确地针对根部材料,并且能够适应根部属性的局部变化。 RooTrak通过将水平集方法与可视跟踪框架相结合来满足这些要求,并且已被证明能够在X射线μCT图像中分割土壤中的多种植物根。该方法提供了高质量的根描述,但是从上到下跟踪根系统,因此省略了向上增长的(斜生的)分支。结果我们提出了RooTrak的扩展,它允许它提取斜生根。另一个向后看的步骤将重新访问以前的图像,标记可能向上生长的根。然后对它们进行跟踪,从而导致根系统的有效和更完整的恢复。结果表明,根部提取明显改善,如果没有,则关键的建筑特征将被低估。结论RooTrak中采用的视觉跟踪框架提供了在X射线CT图像中将根与土壤分离所需的焦点和灵活性,并且可以扩展为检测斜生根。扩展的软件工具可对植物根部结构进行更完整的描述,并支持对建筑性状进行更准确的计算。

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