Int. J. of Information Technology and Management   »   2017 Vol.16, No.1

 

 

Title: PLM as a strategy for the management of heterogeneous information in bio-medical imaging field

 

Authors: Marianne Allanic; Pierre-Yves Hervé; Alexandre Durupt; Marc Joliot; Philippe Boutinaud; Benoît Eynard

 

Addresses:
CADESIS, 37 rue Adam Ledoux, 92400 Courbevoie, France; UMR 5296 GIN CNRS CEA, Université de Bordeaux, 33000 Bordeaux, France; Department of Mechanical Systems Engineering, UMR 7337 Roberval CNRS, Sorbonne Universités, Université de Technologie de Compiègne, CS 60319, 60203 Compiègne Cedex, France
UMR 5296 GIN CNRS CEA, Université de Bordeaux, 33000 Bordeaux, France
Department of Mechanical Systems Engineering, UMR 7337 Roberval CNRS, Sorbonne Universités, Université de Technologie de Compiègne, CS 60319, 60203 Compiègne Cedex, France
UMR 5296 GIN CNRS CEA, Université de Bordeaux, 33000 Bordeaux, France
CADESIS, 37 rue Adam Ledoux, 92400 Courbevoie, France
Department of Mechanical Systems Engineering, UMR 7337 Roberval CNRS, Sorbonne Universités, Université de Technologie de Compiègne, CS 60319, 60203 Compiègne Cedex, France

 

Abstract: The amount of heterogeneous information that researchers in bio-medical imaging (BMI) field have to manage has grown significantly, and their costs remain high. Large-scale sharing and reusing of this information has become unavoidable. Some data management systems have been developed in neuroimaging field, however they miss to integrate the data provenance all along the research works, from study specifications to scientific publication. The manufacturing industry was confronted to similar issues twenty years ago and designed product lifecycle management (PLM) systems to properly share and manage product information all along its lifecycle and among project teams. Therefore, PLM systems are proposed to be a relevant strategy to manage BMI research studies information. The generic, flexible and PLM-oriented data model called BMI-lifecycle management (BMI-LM) is described, as well as a neuroimaging classification which brings flexibility to the information management system. A test implementation into a PLM system is presented, and the feedback from the GIN researchers is discussed.

 

Keywords: biomedical imaging; BMI; product lifecycle management; PLM; information management; heterogeneous information; data modelling; neuroimaging; biomedical images.

 

DOI: 10.1504/IJITM.2017.10001017

 

Int. J. of Information Technology and Management, 2017 Vol.16, No.1, pp.5 - 30

 

Available online: 13 Nov 2016

 

 

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