Code and Data from: Segmenting Root Systems in X-Ray Computed Tomography Images Using Level Sets

This record contains code and data for segmentation using a three-dimensional level-set method, written by Amy Tabb in C++. The record also contains two datasets of root systems in media imaged with X-Ray CT, and the results of running the code on those datasets. The code will also perform a pre-processing task in three-dimensional image sets, and a dataset for that purpose is included as well. This work is a companion to the paper : "Segmenting root systems in X-ray computed tomography images using level sets" (WACV 2018) by the authors or this record, and and open-access version of the paper is here -- https://arxiv.org/abs/1809.06398 . The code is also available from Github: https://github.com/amy-tabb/tabb-level-set-segmentation , using a DOI and stable releases https://doi.org/10.5281/zenodo.3344906. Format of the data: Three input datasets are provided; two for the segmentation functionality of the code, and one to test the pre-processing functionality. The two segmentation sets are the same as were used in the paper, and are CassavaDataset, and SoybeanDataset. The pre-processing set is CassavaSlices. The output set for Soybean is SoybeanResultsJul11. The Cassava result set is large, so I broke it into three compressed folders, CassavaResultsJul12_A, _B, _C. _B is the largest, and only contains the results overwritten on the original X-Ray images. Unless your connection to Zenodo is extremely fast, it will be faster to compute the result than to download it.本数据集记录包含由Amy Tabb使用C++编写的三维水平集（level set）方法分割任务的代码与数据。本记录还包含两份经X射线计算机断层扫描（X-Ray CT）成像的介质内根系数据集，以及将该代码运行于上述数据集后得到的分割结果。该代码同时支持三维图像集的预处理任务，配套的预处理数据集亦包含于本记录中。本工作对应本记录作者团队发表于WACV 2018的论文《Segmenting root systems in X-ray computed tomography images using level sets》，该论文的开放获取版本可通过以下链接获取：https://arxiv.org/abs/1809.06398。本代码亦可通过GitHub仓库https://github.com/amy-tabb/tabb-level-set-segmentation获取，其稳定版本的DOI标识为https://doi.org/10.5281/zenodo.3344906。数据集格式说明：本次共提供三份输入数据集：两份用于测试代码的分割功能，另一份用于测试预处理功能。其中两份分割数据集与论文中使用的完全一致，分别为CassavaDataset（木薯数据集）和SoybeanDataset（大豆数据集）；预处理数据集为CassavaSlices（木薯切片数据集）。大豆数据集的输出结果为SoybeanResultsJul11（7月11日大豆结果集）。木薯结果集体积较大，因此被拆分为三个压缩文件夹：CassavaResultsJul12_A、_B及_C，其中_B体积最大，且仅包含叠加于原始X射线图像之上的分割结果。除非你的Zenodo连接速度极快，否则通过本地计算生成结果会比下载该数据集更为高效。