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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.

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

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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