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Permanent URI for this collectionhttps://repositorio.grial.eu/handle/123456789/34

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Subject: search.filters.subject.Health Platform

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    D-AI-COM: A DICOM Reception Node to Automate the Application of Artificial Intelligence Scripts to Medical Imaging Data
    (Springer, 2024-05-01) Vázquez-Ingelmo, Andrea; García-Holgado, Alicia; García-Peñalvo, Francisco José; Pérez-Sánchez, Pablo; Sánchez-Puente, Antonio; Vicente-Palacio, Víctor; Dorado-Díaz, Pedro Ignacio; Sánchez, Pedro Luis
    Artificial Intelligence (AI) has proven to be useful in several fields. The medical domain is one of the fields that benefits from the application of AI methods to automate and ease complex tasks including disease detection, segmentation, assessment of organ functions, etc. However, applying these kinds of methods to the variety of data formats involved in health contexts is not trivial. It is necessary to provide technologies that enable non-expert users to benefit from AI applications. This work presents a platform that acts as a DICOM reception node with the goal of automating the application of AI algorithms to medical imaging data. This platform is set to ease the process applying AI to their DICOM images by making the whole process transparent and straightforward for users without AI-related or programming skills.
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    KoopaML: Application for receiving and processing DICOM images
    (CEUR-WS.org, 2023-12-05) Fraile-Sanchón, R.; Vázquez-Ingelmo, A.; García-Holgado, A.; García-Peñalvo, F. J.
    AI algorithms application to medical data has gained relevance due to their powerful benefits among different research tasks. However, medical data is heterogeneous and diverse, and these algorithms need technological support to tackle these data management challenges. KoopaML enables users to unify medical data, especially DICOM images and apply AI algorithms to them in a straightforward way through an online web application. This work presents a new feature in the KoopaML platform: a Machine Learning platform to assist non-expert users in defining and applying ML pipelines. The feature comprises the reception, storage, and management of DICOM images. These images are received through a connection with a PACS (Picture Archiving Communication System) system already configured by users on the platform and, after storing the images, it is possible to apply AI algorithms to them and make modifications or annotations.