Fisabio and IGTP lead pioneering studies using artificial intelligence to improve medical diagnostics

• Both organisations sign a framework agreement for scientific collaboration
• Using computational algorithms, they transform medical images into quantitative data to extract information about organs or lesions

The application of artificial intelligence to the analysis of medical images is redefining diagnostic and treatment processes by enabling faster and more accurate assessments of multiple pathologies. In this context, the Fisabio Foundation, an organisation under the Department of Health of the Generalitat Valenciana, and the Germans Trias i Pujol Research Institute (IGTP) have signed a framework agreement for scientific collaboration to jointly promote research in this field.

Their most recent studies focus on the segmentation of medical images, such as MRI or CT scans, identifying and isolating specific areas (such as organs or lesions) for subsequent analysis. In this case, the research is centred on the spinal cord and brain lesions.

"Thanks to artificial intelligence, we are able to automate and optimise procedures that have traditionally been manual and time-consuming, which will make it possible to obtain faster and more accurate results and diagnoses," explains Dr María de la Iglesia, principal investigator of the Unidad Mixta de Imagen Biomédica e Inteligencia Artificial (UMIB-IA) of Fisabio - Centro de Investigación Príncipe Felipe (CIPF).

These studies are supported by the research infrastructures of both institutions, which are equipped with state-of-the-art facilities for medical image processing and the application of artificial intelligence.

For its part, the Computational Anatomy Unit of the Comparative Medicine and Bioimage Centre of Catalonia (CMCiB), a strategic project of IGTP, was established with the aim of meeting different image processing needs, with a specialisation in neuroimaging and radiomics. Within the framework of this collaboration with Fisabio, its work focuses on the segmentation and information extraction for the development and validation of the segmentation process based on deep learning.

"Artificial intelligence opens up new possibilities in medical image analysis, but for it to have a real impact on clinical practice, it is essential to work in a coordinated manner between institutions. This agreement allows us to move in that direction, combining expertise and capabilities to accelerate the translation of these technologies," emphasises Dr Monté-Rubio, Head of Bioimaging and scientific coordinator of the Computational Anatomy Unit (UAC) at CMCiB.

An established partnership

The collaboration between these two institutions began a few years ago with the implementation of the ARIADNA image management platform (short for ARchive of Imaging Data for the Development of New Applications for preclinical and clinical research), which has laid the foundations for new advances in precision medicine.

This joint work is now being further consolidated with the signing of a framework agreement between Fisabio and IGTP, aimed at promoting joint activities, encouraging the exchange of knowledge, providing training for researchers, and developing new technologies in the field of precision medicine.

De la Iglesia welcomes the agreement, stating that "this represents an important step in our mission to consolidate the advances achieved in AI and radiomics to enhance the clinical application of these technologies”.