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

• Published in: Procedia computer science Vol. 108; pp. 1195 - 1204
• Main Authors: Chillarón, Mónica, Vidal, Vicente, Segrelles, Damián, Blanquer, Ignacio, Verdú, Gumersindo
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 2017
• Subjects: Containers; Grid; Medical Imaging; Reconstruction; Reconstruction; Containers; CT; Medical Imaging; Grid
• ISSN: 1877-0509; 1877-0509
• DOI: 10.1016/j.procs.2017.05.065

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.