MOSAIC

Method of Osteo-fracture Study through Automatic Identification and Classification: biomechanical analysis of bone trabecular structure

 Coordinatore  

 Organization address address: Patission Str. 42
city: ATHINA
postcode: 10682

contact info
Titolo: Prof.
Nome: Yannis
Cognome: Vassiliou
Email: send email
Telefono: 302108000000
Fax: 302108000000

 Nazionalità Coordinatore Non specificata
 Totale costo 146˙497 €
 EC contributo 0 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Anno di inizio 2010
 Periodo (anno-mese-giorno) 2010-10-15   -   2012-10-14

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    INSTITUTE OF COMMUNICATION AND COMPUTER SYSTEMS

 Organization address address: Patission Str. 42
city: ATHINA
postcode: 10682

contact info
Titolo: Prof.
Nome: Yannis
Cognome: Vassiliou
Email: send email
Telefono: 302108000000
Fax: 302108000000

EL (ATHINA) coordinator 146˙497.40

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 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

risk    regions    specimens    region    related    structure    tested    mechanically    unbroken    trabecular    prediction    bone    broken    clinical    fracture    classifier    mechanical   

 Obiettivo del progetto (Objective)

'Bone fractures represent a major health problem in the increasingly elder population. The correct prediction of bone fracture risk in bone disease, e.g. osteoporosis, is a mandatory issue for the prevention of traumatic events and related medical efforts. The assessment of the fracture risk is based on the clinical evaluation of bone mineral density, but with an estimation error ranging from 20% to 40%. Trabecular structure is known to play an important role in the mechanical behaviour of bone, but clinical imaging does not provide sufficient information. In order to perform a systematic and in depth analysis of the trabecular framework, and its relation with the mechanical properties, micro-tomographic devices are required. Using these devices, structural analysis of bone specimens could be performed by investigating the structure of the broken region, in order to examine the differences between broken and unbroken regions on specimens that were mechanically tested. The aim of the proposed project is the development of a system that will permit the prediction of in-vitro trabecular mechanical behaviour with possible applications on clinical meso-level x-ray images. The presented system will be comprised mainly of a classifier that will identify the fracture probability of bones’ regions using estimated mechanical parameters. In order to define the classifier, a fracture identification module, based on image processing, will be also developed with the aim to locate firstly broken and unbroken regions of mechanically tested specimens, and then estimate specific mechanical parameters related to the different regions. This initial knowledge will be used to train the classifier and to predict the broken region of not tested bone specimens.'

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