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MAJORIS SIGNED

Majoration-Minimization algorithms for Image Processing

Total Cost €

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EC-Contrib. €

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Partnership

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 MAJORIS project word cloud

Explore the words cloud of the MAJORIS project. It provides you a very rough idea of what is the project "MAJORIS" about.

limiting    too    distributed    optimization    computational    robustness    convergence    algorithm    proposing    scalability    breakthrough    science    medical    big    variables    microscopy    changing    consist    benefit    techniques    designed    reducing    foundations    resolution    least    collected    algorithms    practical    quality    strategies    fly    majoris    tomosynthesis    physical    imaging    astronomy    theoretical    numerical    medicine    physics    acceleration    schemes    acquisition    chemistry    sophisticated    dealing    spectrometry    breast    instruments    action    minimization    solved    solving    employed    data    signal    mind    handling    efficient    majorization    class    context    observation    structure    mm    mathematical    tackle    minimizing    datasets    questions    biology    concerning    analytically    image    tools    inexact    implementations    play    outcomes    versatility    function    relatively    multiphoton    reconstruction    rudimentary    solid    parallel    3d    load    obey    mass    massively    domain    architecture    amounts    proved    constantly    super   

Project "MAJORIS" data sheet

The following table provides information about the project.

Coordinator
INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE 

Organization address
address: DOMAINE DE VOLUCEAU ROCQUENCOURT
city: LE CHESNAY CEDEX
postcode: 78153
website: www.inria.fr

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country France [FR]
 Total cost 1˙500˙000 €
 EC max contribution 1˙500˙000 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2019-STG
 Funding Scheme ERC-STG
 Starting year 2020
 Duration (year-month-day) from 2020-01-01   to  2024-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE FR (LE CHESNAY CEDEX) coordinator 1˙500˙000.00

Map

 Project objective

Mathematical optimization is the key to solving many problems in science, based on the observation that physical systems obey a general principle of least action. While some problems can be solved analytically, many more can only be solved via numerical algorithms. Research in this domain has proved essential over many years. In addition, science in general is changing. Increasingly, in biology, medicine, astronomy, chemistry, physics, large amounts of data are collected by constantly improving signal and image acquisition devices, that must be analyzed by sophisticated optimization tools. In this proposal, we consider handling optimization problems with large datasets. This means minimizing a cost function with a complex structure and many variables. The computational load for solving these problems is too great for even state-of-the-art algorithms. Thus, only relatively rudimentary data processing techniques are employed, reducing the quality of the results and limiting the outcomes that can be achieved via these novel instruments. New algorithms must be designed with computational scalability, robustness and versatility in mind. In this context, Majorization-Minimization (MM) approaches have a crucial role to play. They consist of a class of efficient and effective optimization algorithms that benefit from solid theoretical foundations. The MAJORIS project aims at proposing a breakthrough in MM algorithms, so that they remain efficient when dealing with big data. I propose to tackle several challenging questions concerning algorithm design. These include acceleration strategies, convergence analysis with complex costs and inexact schemes. I will also tackle practical, massively parallel and distributed architecture implementations. Three specific applications are targeted: super-resolution in multiphoton microscopy in biology; on-the-fly reconstruction for 3D breast tomosynthesis in medical imaging; and mass spectrometry data processing in chemistry.

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The information about "MAJORIS" are provided by the European Opendata Portal: CORDIS opendata.

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