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Titolo:
Algorithms for radiological image registration and their clinical application
Autore:
Hawkes, DJ;
Indirizzi:
Unitedputat& Dent Sch Guys & St Thomas Hosp, Guys Hosp, Div Radiol Sci, Com United Med & Dent Sch Guys & St Thomas Hosp London England SE1 9RT , Com
Titolo Testata:
JOURNAL OF ANATOMY
, volume: 193, anno: 1998,
parte:, 3
pagine: 347 - 361
SICI:
0021-8782(199810)193:<347:AFRIRA>2.0.ZU;2-#
Fonte:
ISI
Lingua:
ENG
Soggetto:
VOXEL SIMILARITY MEASURES; 3-DIMENSIONAL REGISTRATION; AUTOMATED ALGORITHM; MR-IMAGES; CT IMAGES; BRAIN; PET; SURGERY;
Keywords:
image registration; image transformation; radiological imaging;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
49
Recensione:
Indirizzi per estratti:
Indirizzo: Hawkes, DJ Unitedputat& Dent Sch Guys & St Thomas Hosp, Guys Hosp, Div Radiol Sci, Com United Med & Dent Sch Guys & St Thomas Hosp 5th Floor,Thomas Guy House,London Bridge London England SE1 9RT
Citazione:
D.J. Hawkes, "Algorithms for radiological image registration and their clinical application", J ANAT, 193, 1998, pp. 347-361

Abstract

This paper reviews recent work in radiological image registration and provides a classification of image registration by type of transformation and by methods employed to compute the transformation. The former includes transformation of 2D images to 2D images of the same individual, transformation of 3D images to 3D images of the same individual, transformation of images to an atlas or model, transformation of images acquired from a number of individuals, transformations for image guided interventions including 2D to 3D registration and finally tissue deformation in image guided interventions. Recent work on computing transformations for registration using corresponding landmark based registration, surface based registration and voxel similarity measures, including entropy based measures, are reviewed and compared. Recently fully automated algorithms based on voxel similarity measures and, in particular, mutual information have been shown to be accurate and robust at registering images of the head when the rigid body assumption is valid. Two approaches to modelling soft tissue deformation for applications in image guided interventions are described. Validation of complex processing tasks such as image registration is vital if these algorithms are to be used in clinical practice. Three alternative validation strategies are presented. These methods are finding application outside the original domain of radiological imaging.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 05/04/20 alle ore 22:43:02