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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.

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

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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