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Image-to-Image-Translation for Data Calibration in Brain Stroke Microwave Imaging

Project description

Advancing brain stroke diagnosis with improved microwave imaging

Stroke is a leading cause of death and disability in the EU. Microwave imaging (MWI) shows promise for stroke diagnosis due to its non-invasive, low-cost, and portable nature. However, data calibration currently requires a physical phantom of the patient’s head, posing challenges. Supported by the Marie Skłodowska-Curie Actions programme, the I2I-StrokeCal project will develop a novel calibration method based solely on patient measurements, removing the need for phantoms. It will produce the first brain MWI dataset and create an image-to-image (I2I) translation tool to calibrate both synthetic and experimental data using advanced computer vision techniques.

Objective

Stroke is a leading cause of death and disability in the European Union. The use of microwave imaging (MWI) for brain stroke diagnosis has attracted growing interest in the past decade thanks to its non-invasiveness and low costs. Furthermore, thanks to its portability, brain MWI holds significant promise for widespread adoption in-ambulance, dramatically reducing intervention time. Data calibration still holds a strong limit to this application, where the need for a physical phantom of the patient head is the main bottleneck.

I2I-StrokeCal will develop and validate a novel method to perform data calibration relying solely on the patient measurement, thus without additional phantom measurements. This step-change will be attained through 3 specific objectives: (O1) development of the first dataset of brain MWI data in the literature; (O2) training and test of an image-to-image translation (I2I) tool which calibrates synthetically generated MWI data; (O3) training and test of the final I2I model which calibrates experimental MWI data. The proposed methodology applies cutting-edge computer vision techniques (I2I) to address a MWI problem (data calibration) applied to the medical field (stroke diagnosis).

The main host will be POLITO, home to the most advanced brain MWI prototype (TRL-4) within academia. The fellowship will also include two 4-months secondments. The first will be at the University of Manitoba (Canada), where the Researcher will be trained on the integration between machine learning and inverse scattering. The second will be at the École Polytechnique (France), to gain experience on machine learning and computer vision. The results will then be exploited during a 6-months non-academic placement at UBT S.r.l an Italian startup that is conducting clinical trials with a TRL-6 brain MWI prototype. The acquired skills will shape the Researcher into a mature, independent scientist with interdisciplinary expertise and international recognition in medical MWI.

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2024-PF-01

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Coordinator

POLITECNICO DI TORINO
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 242 054,10
Address
CORSO DUCA DEGLI ABRUZZI 24
10129 Torino
Italy

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Region
Nord-Ovest Piemonte Torino
Activity type
Higher or Secondary Education Establishments
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Total cost

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