Project description
Smart ultrasound imaging
Ultrasound localisation microscopy (ULM) is an advanced imaging method that uses tiny gas-filled bubbles called microbubbles as contrast agents to visualise blood vessels. ULM provides much higher resolution than standard ultrasound. However, current ULM techniques are limited by long scan times and the need for very high frame rates, making them difficult to use in clinical settings. With the support of the Marie Skłodowska-Curie Actions programme, the ULMARM project aims to improve image reconstruction using AI and mathematical modelling. These tools will make ULM faster and more accurate, enabling clearer and more detailed ultrasound images that could improve the diagnosis and monitoring of diseases in everyday medical practice.
Objective
The ULMARM, or Ultrasound Localization Microscopy with Advanced Reconstruction Models, seeks to improve ultrasound imaging by addressing key challenges in Ultrasound Localization Microscopy (ULM). Traditional ULM methods require long acquisition times and ultra high frame rates to track microbubbles (MBs) accurately, stretching the capabilities of current clinical ultrasound systems. ULMARM aims to solve these challenges by developing advanced reconstruction techniques and integrating deep learning (DL) models. The goal is to relax frame rate demands while maintaining high-quality super-resolved imaging and accurate motion tracking, making ULM more feasible for clinical applications. In ULMARM, I propose recasting ULM as a mathematical inverse problem to achieve super-resolution in both space and time jointly. By treating the relationship between MB movement and ultrasound frames as a generative forward model, I will infer the most probable MB trajectories from observations using a Bayesian posterior maximization approach. To tackle inherent challenges, I will utilize advanced deep generative models and strong data-driven priors to streamline the inference process. The ULMARM project is organized into six work packages (WPs). WP1 focuses on new sparse coding methods to relax frame rate while preserving image quality. WP2 develops mathematical models for direct reconstruction, including motion compensation for improved accuracy. WP3 uses DL to reconstruct missing data, improving both spatial and temporal resolution. WP4 extends these methods to 3D ULM, tackling challenges like high volume rates and out-of-plane motion. WP5 focuses on evaluating these techniques with experimental and clinical datasets. WP6 handles project management and training. The MSCA Fellowship will provide crucial resources and collaboration opportunities, helping me advance my research in ULMARM, establish innovative techniques to improve ULM’s clinical use, and career development.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences physical sciences optics microscopy super resolution microscopy
- natural sciences physical sciences acoustics ultrasound
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2024-PF-01
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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.
5612 AE Eindhoven
Netherlands
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