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Combining Grid Computing and Docker Containers for the Study and Parametrization of CT Image Reconstruction Methods

机译:CT图像重建方法的研究和参数化组合网格计算机容器

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Computed tomography (CT) is one of the most widely used methods in Medical Imaging. Despite of its relevance in the diagnosis of diseases with a high impact in our society (such as cancer), it is one of the most potentially harmful modalities. CT requires a high X-ray dose to be induced to the patients. Solving the CT Image Reconstruction problem iteratively in order to approximate the solution allows working with only a subset of the input data required by direct methods. This directly implies a reduction of the radiation received by the patient and a strong reduction on the potential morbidity. Therefore, we aim to study the feasibility of such methods for their actual application, with the purpose of concluding if they are accurate and can obtain good quality images with a lower dose of X rays. This paper discusses the use of containers within a Grid Computing platform to perform a thorough study of all the possible configurations and parameters of various methods being developed to reconstruct CT images iteratively, which could lead to find the optimal configuration of the parameters. The work compares two approaches for managing the software dependencies of the code: store the software libraries on a Storage Element and using containers for executing the job.
机译:计算机断层扫描(CT)是医学成像中使用最广泛的方法之一。尽管其在诊断对社会(如癌症)的影响很高的疾病方面存在相关性,但它是最有害的方式之一。 CT需要诱导患者的高X射线剂量。迭代地解决CT图像重建问题,以近似求解允许仅使用直接方法所需的输入数据的子集。这直接意味着减少患者接收的辐射和强烈降低潜在发病率。因此,我们的目标是研究这种方法的实际应用的可行性,目的是结束如果它们是准确的,并且可以获得具有较低剂量的X射线的良好质量图像。本文讨论了在网格计算平台内使用容器的使用,以便对正在开发的各种方法的所有可能的配置和参数进行全面研究以迭代地重建CT图像,这可能导致找到参数的最佳配置。该工作比较了两种用于管理代码的软件依赖性的方法:将软件库存储在存储元素上并使用容器执行作业。

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