A root auto tracing and analysis ( <scp>ARATA</scp> ): An automatic analysis software for detecting fine roots in images from flatbed optical scanners
A root auto tracing and analysis ( <scp>ARATA</scp> ): An automatic analysis software for detecting fine roots in images from flatbed optical scanners
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根部自动追踪和分析 ( <scp>ARATA</scp> )：一种自动分析软件，用于检测平板光学扫描仪图像中的细根
DOI：
10.1111/2041-210x.13972
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发表时间：
2022
影响因子：
6.6
通讯作者：
Dannoura Masako
中科院分区：
文献类型：
--
作者：
Yabuki Arata;Ikeno Hidetoshi;Dannoura Masako
埋地扫描仪经常被用来研究细根动态连续观察他们在一个固定的点拍摄的图像。因此，已经开发了软件来支持操作者从扫描图像中定量分析细根。然而，图像处理仍然是一项耗时的工作。作为一种以像素为单位识别物体的方法，深度学习已经取得了令人印象深刻的结果。在本研究中，我们尝试使用卷积神经网络实现细根图像分析的自动化。使用根自动跟踪和分析（阿拉塔），我们成功地从扫描图像中提取了细根，并计算了细根的投影面积，用于长期动态。我们的软件可以自动处理在不同研究地点获得的扫描图像，并加速细根动态的长期研究。
Buried scanners are often used to study fine root dynamics by continuously observing them from the images taken at a fixed point. Accordingly, software have been developed to support operators to quantitatively analyse fine roots from scanned images. However, image processing is still time‐consuming work.Deep learning has achieved impressive results as a method for recognising objects in pixel units. In this study, we attempted to automate the image analysis of fine roots using convolutional neural network.Usinga root auto tracing and analysis(ARATA), we succeeded in extracting fine roots from scanned images and calculated projected area of fine roots for long‐term dynamics.Our software enables the automatic processing of scanned images acquired at various study sites and accelerates the study of fine root dynamics over extended time periods.