Project description
Two tracers for better brain imaging
Positron Emission Tomography (PET) is a medical imaging technique that exposes in vivo brain-wide metabolic processes. Before PET image acquisition, a tracer is injected into the patient. PET image acquisition is limited to one tracer, thus only displaying one metabolic process in the brain. 'Dual tracer' PET images give novel insights for new drugs for Alzheimer's and increase understanding of the brain. The EU-funded Dual Tracer PET project will use machine learning techniques to develop and implement a reconstruction algorithm for dual tracer PET resulting in two separate PET images with high image quality. The results will help in understanding neuronal communication in the brain.
Objective
Positron Emission Tomography (PET) is a medical imaging technique that displays in vivo brain-wide metabolic processes. Prior to PET image acquisition, a tracer, labelled with a positron emitting isotope, is injected to the patient. This so-called radiotracer distributes over the body and accumulates in e.g. inflammatory tissue.
To date, the acquisiton of a PET image is limited to one tracer, thereby only displaying one metabolic process in the brain. However, the acquisition of two separate PET images acquired with different tracer simultaneously would give novel and unique insights in the communication between e.g. neurotransmitter systems. These insights could be used for the development of new drugs for e.g Alzheimer patients and would increase the understanding of the healthy and diseased brain.
The acquisition of 'dual tracer' PET images can be achieved by combining two radiotracers with different properties: The first 'standard' radiotracer emits two photons that are recorded by the PET system, while the second 'non-standard' tracer emits two photons and an additional gamma ray. By identifying the additional gamma ray, the photon detections of the two tracers can be separated and two PET images can be reconstructed.
'Dual tracer' PET image reconstruction yields challenges due to undesirable effect of photon detection. In this project, a machine learning algorithm will be trained to detect and correct for these effects. Moreover, the image acquired with the 'non-standard' tracer yields low image quality. A Convolutional Neural Network will be trained to denoise this PET image.
In the proposed project, a reconstruction algorithm for dual tracer PET based on machine learning techniques and resulting in two separate PET images with high image quality will be developed and implemented. The proposed project will demonstrate if dual tracer PET imaging has future potential and will help to understand the highly interactive neuronal communication in the brain.
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.
- medical and health sciences basic medicine neurology dementia alzheimer
- natural sciences physical sciences theoretical physics particle physics photons
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
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.
-
HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
See all projects funded under this programme
Topic(s)
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.
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
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2021-PF-01
See all projects funded under this callCoordinator
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.
52428 JULICH
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.