FCCA

Five Challenges in Computational Anatomy

Coordinatore	IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE    more Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.
Nazionalità Coordinatore	United Kingdom [UK]
Totale costo	1˙740˙000 €
EC contributo	1˙740˙000 €
Programma	FP7-IDEAS-ERC Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	ERC-2010-AdG_20100224
Funding Scheme	ERC-AG
Anno di inizio	2011
Periodo (anno-mese-giorno)	2011-05-01   -   2016-04-30

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE  Organization address address: SOUTH KENSINGTON CAMPUS EXHIBITION ROAD city: LONDON postcode: SW7 2AZ contact info Titolo: Ms. Nome: Brooke Cognome: Alasya Email: send email Telefono: +44 207 594 1181 Fax: +44 207 594 1418	UK (LONDON)	hostInstitution	1˙740˙000.00
2	IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE  Organization address address: SOUTH KENSINGTON CAMPUS EXHIBITION ROAD city: LONDON postcode: SW7 2AZ contact info Titolo: Prof. Nome: Darryl Cognome: Holm Email: send email Telefono: +44 20 7594 8531	UK (LONDON)	hostInstitution	1˙740˙000.00

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 Obiettivo del progetto (Objective)

'New medical imaging technologies encode human anatomy in a wide variety of data structures. Computational Anatomy (CA) offers an approach to synthesize this plethora of data by comparison of anatomical features using smooth invertible transformations specific to the data structure. This proposal is for work to develop new mathematical and numerical methods for image analysis in the framework of CA, aimed at meeting the following five challenges in image analysis for the comparison and interpolation of shapes in biomedical images of the heart and the brain. 1. Data structure: Develop a unified approach for registering images encoded in a wide variety of data structures. The unifying concept in our approach is the momentum map, a fundamental concept from the theory of Lie group transformations. 2. Data fusion: After placing the transformations of the variety of data structures into the same conceptual framework using momentum maps, synthesise (fuse) their multiple modalities of information by accounting for the different transformation properties of the different data structures under smooth invertible maps. 3. Multiple resolutions: Develop the momentum map framework to enable registration of data at multiple resolutions by concatenating the Lie group transformations that define the momentum maps. 4. Time-varying (4D) images: Treat time-varying images in this geometric framework by matching snapshots in time using geodesic splines that interpolate the image snapshot from one time to another. Quantity the effects of noise and uncertainty in 4D image analysis. 5. Changes in image topology: Extend the transformative approach to allow changes in topology in passing between images by using the method of metamorphosis. Simply put, the five challenges are: to 1. register images of different data structures and 2. combine them, even at 3. different resolutions; then do the same things with 4. splines and 5. metamorphosis, including noise.'