Cone-Beam Computed Tomography Dataset of a Pine Cone
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Summary This dataset is a collection of X-ray projection images of a pine cone imaged in a cone-beam computed tomography (CBCT) scanner. The dataset also includes a metadata file, specifying the scan geometry and other important scan parameters, and a photograph of the sample. Description Sample Information The sample is an open cone of a Baltic pine (Pinus sylvestris), approximately 3 cm in diameter. For the scanning process sticky tack was used to attach the sample to a plastic tube placed into the rotation stage. Scanner The measurements were acquired using a cone-beam computed tomography scanner designed and constructed in-house in the Industrial Mathematics Computed Tomography Laboratory at the University of Helsinki. The scanner consists of a molybdenum target X-ray tube (Oxford Instruments XTF5011), a motorized rotation stage (Thorlabs CR1-Z7), and a 12-bit, 2240x2368 pixel, energy-integrating flat panel detector (Hamatsu Photonics C7942CA-22). Scan Settings 721 X-ray projections were acquired using an angle increment of 0.5 degrees. The X-ray source voltage and tube current were set at 40 kV and 1 mA, respectively. The exposure time of the flat panel detector was set to 1000 ms. Data Post-Processing Two correction images were acquired before scanning the sample. A dark current image was created by averaging 100 images taken with the X-ray source off. A flat-field image was created by averaging 100 images taken with the X-ray source switched on with no sample placed in the scanner. After the scan, dark current and flat-field corrections were applied to each projection image using the Hamamatsu HiPic imaging software version 9.3. Data Format The X-ray projections are stored in .tif format. The metadata is contained in .txt file with formatting that is both human-readable and machine-readable. Notes Due to a slightly misaligned center of rotation in the scanner, the CT reconstructions can appear blurry. It was empirically observed that this problem can be compensated for quite well by shifting each projection left by 5 pixels, using circular boundary conditions, before performing any other operations on the projections. Research Group This dataset was produced by the Inverse Problems research group at the Department of Mathematics and Statistics at the University of Helsinki, Finland: https://www2.helsinki.fi/en/researchgroups/inverse-problems. Additional Links This dataset was originally created as part of a tutorial on working with measured X-ray data in computed tomography. A video tutorial on the measurement process can be found on the Inverse Problems Channel on YouTube at https://www.youtube.com/watch?v=CWUomAmUDys. To get started with the data, we recommend looking at the HelTomo toolbox, specifically created for working with CBCT data collected in the Industrial Mathematics Computed Tomography Laboratory, and available at https://github.com/Diagonalizable/HelTomo Contact Details For more information or guidance in using these datasets, please contact alexander.meaney [at] helsinki.fi.
摘要：本数据集为一批松果的锥束计算机断层扫描（CBCT）投影图像，采集自一台锥束计算机断层扫描扫描仪。数据集还包含一份元数据文件，用于记录扫描几何结构及其他关键扫描参数，同时附带一份样本实拍照片。 描述 样本信息：该样本为一棵欧洲赤松（Pinus sylvestris）的开裂松果，直径约3厘米。扫描过程中，采用黏贴橡皮泥将样本固定至置于旋转台的塑料管上。 扫描仪：本次测量使用的锥束计算机断层扫描扫描仪由赫尔辛基大学工业数学计算机断层扫描实验室自主设计并搭建。该扫描仪包含钼靶X射线管（Oxford Instruments XTF5011）、电动旋转台（Thorlabs CR1-Z7），以及一款12位、分辨率2240×2368像素的能量积分型平板探测器（Hamamatsu Photonics C7942CA-22）。 扫描设置：共采集721张X射线投影图像，角度步长为0.5度。X射线源电压与管电流分别设置为40 kV与1 mA。平板探测器的曝光时长设置为1000 ms。 数据后处理：扫描样本前，需采集两张校正图像。暗电流图像通过采集X射线源关闭状态下的100张图像并取平均得到；平场校正图像通过采集X射线源开启且扫描仪内无样本时的100张图像并取平均得到。扫描完成后，使用滨松HiPic成像软件V9.3对每张投影图像进行暗电流与平场校正。 数据格式：X射线投影图像以.tif格式存储。元数据存储于.txt文件中，其格式兼具人类可读性与机器可读性。 备注：由于扫描仪的旋转中心存在轻微偏移，CT重建图像可能出现模糊现象。经实验验证，在对投影图像进行其他操作前，采用圆形边界条件将每张投影左移5像素，可较好地补偿该问题。 研究团队：本数据集由芬兰赫尔辛基大学数学与统计系逆问题研究小组制作，相关网址：https://www2.helsinki.fi/en/researchgroups/inverse-problems。 附加链接：本数据集最初作为计算机断层扫描实测X射线数据处理教程的一部分创建。关于扫描过程的视频教程可在YouTube的逆问题频道查看，网址：https://www.youtube.com/watch?v=CWUomAmUDys。如需上手该数据集，推荐使用专为工业数学计算机断层扫描实验室采集的锥束CT数据开发的HelTomo工具箱，其开源地址为：https://github.com/Diagonalizable/HelTomo。 联系方式：如需获取更多信息或使用该数据集的相关指导，请联系alexander.meaney [at] helsinki.fi。
