Medical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.
Med Phys. 2018 Nov;45(11):5343-5351. doi: 10.1002/mp.13174. Epub 2018 Oct 1.
The aim of this paper is to provide a novel, publicly available standard image dataset with a useful evaluation framework for assessing nonrigid two-/three-dimensional (2D/3D) registration algorithms.
A pig lung model was used to obtain the image dataset. Inflated with different amounts of oxygen, a sequence of 3D volume data was acquired with computed tomography (CT), which ideally simulated different respiratory phases. With the model inflated and kept in certain states, 3D CT, 2D CT scout image and 2D x-ray were acquired for the same respiratory phases, making them suitable to establish the evaluation dataset for 2D/3D registration algorithms. A total of 120 well-distributed landmarks in every 3D volume were manually annotated and checked by several radiologists using semi-automatic software to generate the dataset.
All 3D image data were stored in both DICOM and ITK Meta format, and 2D image data were stored in DICOM format. A total of 120 landmarks were manually annotated for each 3D image. Among these landmarks, eight landmarks located on large branch of the bronchial tree were also annotated in 2D images. The landmark coordinates were stored in a text file. The detailed usage including a standard evaluation framework for the proposed dataset is also provided. The dataset can be downloaded from the Zenodo repository (https://doi.org/10.5281/zenodo.997887).
Our standard dataset was acquired with advanced clinical imaging devices and is quite suitable for quantitatively evaluating state-of-art, nonrigid 2D/3D registration algorithms.
本文旨在提供一个新颖的、公开可用的标准图像数据集，并提供一个有用的评估框架，用于评估非刚性二维/三维（2D/3D）配准算法。
使用猪肺模型获得图像数据集。通过计算机断层扫描（CT）对其进行充气，充气量不同，以理想地模拟不同的呼吸阶段，获取一系列 3D 体积数据。在模型充气并保持在一定状态下，获取相同呼吸阶段的 3D CT、2D CT 扫描图像和 2D X 射线，使其适合建立 2D/3D 配准算法的评估数据集。总共在每个 3D 体积中手动注释了 120 个分布均匀的地标，并由几位放射科医生使用半自动软件进行检查，以生成数据集。
所有 3D 图像数据均以 DICOM 和 ITK Meta 格式存储，2D 图像数据以 DICOM 格式存储。每个 3D 图像都手动注释了 120 个地标。在这些地标中，有 8 个地标位于支气管树的大分支上，也在 2D 图像上进行了注释。地标坐标存储在一个文本文件中。还提供了有关建议数据集的详细使用说明，包括标准评估框架。该数据集可从 Zenodo 存储库（https://doi.org/10.5281/zenodo.997887）下载。
我们的标准数据集是使用先进的临床成像设备获取的，非常适合定量评估最先进的非刚性 2D/3D 配准算法。
