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Advanced analysis of multiparametric volumetric ultrafast ultrasound: a novel approach for non-invasive breast cancer diagnosis

CORDIS · observation · Publication date unknown

ent of tissue stiffness, fiber organization, and vascular mapping, all relevant to tumour development. In this project, I propose a new approach to diagnosing breast cancer non-invasively by applying machine learning analysis to rich volumetric multiparametric maps of complementary tumour aspects, obtained using these innovative ultrafast ultrasound techniques. The project will tackle the technological challenge of integrating these techniques into a common acquisition and analysis framework, and include the collection of a large clinical dataset and the development and validation of a predictive malignancy model informing on tumour characteristics for the diagnosis. This approach will open the door to fully virtual biopsies, impacting society on a large scale in terms of cost, diagnostic efficacy, and patient comfort. machine learning, predictive models, breast cancer diagnosis, ultrafast ultrasound imaging, 3D ultrasound imaging, ultrasound biomarkers

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recordType

award

status

SIGNED

region

EU

value

1499498

unit

EUR