Label Image Ground Truth Data for Lumbar Spine MRI Dataset

This dataset contains the raw label images and ground truth label images of axial view slices of lumbar spine MRI used to train SegNet to detect lumbar spinal stenosis. The four labelled Regions of Interest namely 1) Intervertebral Disc (IVD), 2) Posterior Element (PE), 3) Thecal Sac (TS) and 4) the Area between Anterior and Posterior (AAP) vertebrae elements. The labelling process was carried out by five labellers under supervision of an expert radiologist using the T1-weighted axial-view MRI slice of the last three IVDs. Analysis on the quality of the developed ground truth label images is provided in our paper. You can download and read the research papers detailing our methodology on boundary delineation for lumbar spinal stenosis detection using the URLs provided in the Related Links at the end of this page. You can also check out other dataset and source code related to this program from that section. We kindly request you to cite our papers when using our data or program in your research.本数据集包含用于训练SegNet以检测腰椎管狭窄症的腰椎磁共振成像（Magnetic Resonance Imaging, MRI）轴位切片的原始标注图像与真值标注图像。本次标注共涵盖四类感兴趣区域（Regions of Interest, ROI），分别为1）椎间盘（Intervertebral Disc, IVD）、2）后部结构（Posterior Element, PE）、3）硬膜囊（Thecal Sac, TS）以及4）椎体前后区域（Area between Anterior and Posterior, AAP）。标注工作由五名标注人员在一名放射学专家的监督下完成，所用数据集为最后三个椎间盘的T1加权轴位MRI切片。本数据集所生成的真值标注图像的质量分析已在我们的研究论文中予以阐述。您可通过本页面末尾相关链接中提供的网址，下载并阅读详细阐述我们用于腰椎管狭窄症检测的边界勾画方法的研究论文。您亦可从该板块获取本项目相关的其他数据集与源代码。我们恳请您在研究中使用本数据集或本项目程序时引用我们的研究论文。