Catalogo Articoli (Spogli Riviste)

OPAC HELP

Titolo:
Automatic segmentation of the ventricular system from MR images of the human brain
Autore:
Schnack, HG; Pol, HEH; Baare, WFC; Viergever, MA; Kahn, RS;
Indirizzi:
Univ Utrecht, Med Ctr, Dept Psychiat, NL-3584 CX Utrecht, Netherlands UnivUtrecht Utrecht Netherlands NL-3584 CX 3584 CX Utrecht, Netherlands Univ Utrecht, Med Ctr, Image Sci Inst, Utrecht, Netherlands Univ Utrecht Utrecht Netherlands , Image Sci Inst, Utrecht, Netherlands
Titolo Testata:
NEUROIMAGE
fascicolo: 1, volume: 14, anno: 2001,
parte:, 1
pagine: 95 - 104
SICI:
1053-8119(200107)14:1<95:ASOTVS>2.0.ZU;2-S
Fonte:
ISI
Lingua:
ENG
Soggetto:
TEMPORAL HORN; SCHIZOPHRENIA; ABNORMALITIES; MORPHOLOGY; ASYMMETRY; DISORDER; VOLUMES; ANATOMY;
Keywords:
segmentation; ventricle; brain;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
38
Recensione:
Indirizzi per estratti:
Indirizzo: Schnack, HG Univ Utrecht, Med Ctr, Dept Psychiat, A01-126,Heidelberglaan 100, NL-3584 CX Utrecht, Netherlands Univ Utrecht A01-126,Heidelberglaan 100Utrecht Netherlands NL-3584 CX
Citazione:
H.G. Schnack et al., "Automatic segmentation of the ventricular system from MR images of the human brain", NEUROIMAGE, 14(1), 2001, pp. 95-104

Abstract

An algorithm was developed that automatically segments the lateral and third ventricles from T1-weighted 3-D-FFE MR images of the human brain. The algorithm is based upon region-growing and mathematical morphology operators and starts from a coarse binary total brain segmentation, which is obtainedfrom the 3-D-FFE image. Anatomical knowledge of the ventricular system hasbeen incorporated into the method in order to find all constituting parts of the system, even if they are disconnected, and to avoid inclusion of nonventricle cerebrospinal fluid (CSF) regions. A test of the method on a synthetic MR. brain image produced a segmentation overlap of 0.98 between the simulated ventricles ("model") and those defined by the algorithm. Further tests were performed on a large data set of 227 1.5 T MR brain images. The algorithm yielded useful results for 98% of the images, The automatic segmentations had intraclass correlation coefficients of 0.996 for the lateral ventricles and 0.86 for the third ventricle, with manually edited segmentations. Comparison of ventricular volumes of schizophrenia patients compared with those of healthy control subjects showed results in agreement with the literature. (C) 2001 Academic Press.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 25/02/20 alle ore 08:03:20