Management and Application of AI to DICOM Image Processing: A Systematic Mapping Literature Review

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dc.contributor.authorFraile-Sanchón, Rubén
dc.contributor.authorVázquez-Ingelmo, Andrea
dc.contributor.authorGarcía-Peñalvo, Francisco José
dc.contributor.authorGarcía-Holgado, Alicia
dc.date.accessioned2026-05-15T11:43:09Z
dc.date.issued2024-07-15
dc.description.abstractArtificial intelligence (AI) has the potential to bring unprecedented benefits to humankind. Therefore, it is worth investigating how to maximize these benefits while avoiding potential pitfalls. Given this context, the first task necessary to assess the potential of this approach is to understand the management landscape and the application of AI to DICOM image processing. In this case, the researchers employ a systematic mapping review. This paper presents this process and its main findings. 35 studies have been selected from a total of 154 analyzed. From them, in addition to obtaining a clear view of the application of AI to DICOM images, we can also conclude that pre-trained AI algorithms are used in a higher amount than non-trained algorithms in terms of DICOM image usage.
dc.identifier.citationFraile-Sanchón, R., Vázquez-Ingelmo, A., García-Peñalvo, F. J., & García-Holgado, A. (2024). Management and Application of AI to DICOM Image Processing: A Systematic Mapping Literature Review. In J. A. Carvalho Gonçalves, J. L. Sousa de Magalhães Lima, J. P. Coelho, F. J. García-Peñalvo, & A. García-Holgado (Eds.), Proceedings of TEEM 2023. The Eleventh International Conference on Technological Ecosystems for Enhancing Multiculturality (Bragança, Portugal, 25-27 October 2023) (pp. 345–355). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-1814-6_34
dc.identifier.urihttps://repositorio.grial.eu/handle/123456789/3306
dc.language.isoen
dc.publisherSpringer
dc.subjectArtificial Intelligence
dc.subjectalgorithms
dc.subjectDICOM
dc.subjectpre-trained
dc.subjectsegmentation
dc.titleManagement and Application of AI to DICOM Image Processing: A Systematic Mapping Literature Review
dc.typeArticle

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