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This tool has been developed by Eurecat in collaboration with the Vall d’Hebron Campus and was coordinated by the Hospital's Diagnostic Imaging Department within the framework of the Deep Lung project.
The Vall d’Hebron Campus, in collaboration with the Eurecat technology centre, has created a new system for identifying nodules that are indicative of possible lung cancers using a tool based on AI techniques, particularly Deep Learning. The project has been supported by the Centre of Innovation for Data Tech and Artificial Intelligence (CIDAI). Eurecat showcased this new technology at this year's Mobile World Congress.
The technology allows for the refinement of predictive models based on 3D medical imaging, integrated within the radiology workflow, with the aim of “enabling the early detection of the disease and providing a support tool for the prognosis and follow-up by expert medical professionals, representing a breakthrough in precision medicine that is transforming clinical practice and the healthcare sector”, explains Felipe Miralles, director of the Eurecat Digital Health Unit.
The innovation seeks to support radiologists in the monitoring of lung nodules by means of a system that is capable of conducting analyses via Deep Learning; detecting nodules and re-identifying them; and providing a projection of tumour growth and the probability of said tumours being cancerous.
An important aspect of this innovation is the creation of an interface for the temporal analysis of lung nodules and the intuitive and informative visual examination of the results, which helps physicians to provide more accurate diagnoses.
This tool has been developed by Eurecat in collaboration with the Vall d'Hebron Campus, and was coordinated by the Hospital’s Clinical Directorate of Diagnostic Imaging and Nuclear Medicine within the framework of the Deep Lung project. “The aim is to develop an artificial intelligence (AI) tool applied to CT images that will allow for the early detection of lung cancer. This tool is based on the monitoring of suspicious lesions, which are evaluated by radiology specialists at Vall d’Hebron University Hospital. The application of AI in these cases will improve the diagnostic and predictive capacity in patients affected by the disease, and in future screening programmes for lung cancer in the wider population”, concluded Dr Manel Escovar, Clinical Director of the Diagnostic Imaging Department at Vall d'Hebron University Hospital and researcher in the Molecular Medical Imaging Research Group at the Vall d'Hebron Research.
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