CT scan data underlying the PhD dissertation: Numerical and deep learning algorithms for automated quality assurance in proton therapy

The dataset contains CT scans used as input for the algorithm developed in chapters 2 and 3 of the dissertation. Using a CT scan and a treatment plan as inputs, dose and dose change computations in regions of interest can be performed. Specifically, the dataset contains:<br>a head and neck CT scan obtained from the CORT dataset [1],a prostate CT scan obtained from the Cancer Imaging Archive [2],and multiple self-made custom water box CT scans. In addition to a homogeneous water box CT scan (i.e., a cube with uniform 0 Hounsfield Units (HU) composition), there are scans where a slab with half the side-length of the cube and composition of either bone (1000 HU) or air (-1000 HU) is inserted in the water box at varying distances from the middle point.<br>All the scans consist of CT slices and are stored in the DICOM format. To correctly read, relate to each other and further process the different CT slices, appropriate DICOM reading software (e.g., the pydicom Python package) must be used. <br>References:[1] - Craft, D., Bangert, M., Long, T., Papp, D., &amp; Unkelbach, J. (2014). <em>Supporting material for: "Shared data for IMRT optimization research: the CORT dataset"</em> [Data set]. GigaScience Database. https://doi.org/10.5524/100110[2] - Yorke, A. A., McDonald, G. C., Solis, D., &amp; Guerrero, T. (2019). <strong>Pelvic Reference Data (Version 1) [Data set].</strong> The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.2019.WOSKQ5OO

本数据集包含本论文第2、3章所开发算法的输入用CT扫描影像。该算法以CT扫描与治疗计划作为输入，可对感兴趣区域内的剂量及剂量变化开展计算。
具体而言，本数据集包含：取自CORT数据集[1]的头颈部CT扫描影像、取自癌症影像档案库（Cancer Imaging Archive）[2]的前列腺CT扫描影像，以及多份自制定制水模CT扫描影像。
除均匀水模CT扫描（即由亨氏单位（Hounsfield Unit, HU）为0的均匀物质构成的立方体）外，本数据集还包含在水模中距中心点不同距离处，嵌入一块边长为原立方体一半、成分为骨（1000 HU）或空气（-1000 HU）的平板的扫描影像。
所有扫描影像均为CT断层切片，以DICOM（Digital Imaging and Communications in Medicine）格式存储。若需正确读取各CT切片、建立相互关联并开展后续处理，需使用适配的DICOM读取软件（例如Python的pydicom库）。
参考文献：
[1] Craft, D., Bangert, M., Long, T., Papp, D., & Unkelbach, J. (2014). 支持材料：《用于调强放射治疗（Intensity-Modulated Radiation Therapy, IMRT）优化研究的共享数据：CORT数据集》[数据集]. GigaScience数据库. https://doi.org/10.5524/100110
[2] Yorke, A. A., McDonald, G. C., Solis, D., & Guerrero, T. (2019). 《盆腔参考数据（版本1）》[数据集]. 癌症影像档案库. https://doi.org/10.7937/TCIA.2019.WOSKQ5OO