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A new computer-aided diagnostic tool for non-invasive characterisation of malignant ovarian masses: results of a multicentre validation study.

par Lucidarme, Olivier;Akakpo, Jean-Paul;Granberg, Seth;Sideri, Mario;Levavi, Hanoch;Schneider, Achim;Autier, Philippe;Nir, Dror;Bleiberg, Harry ;Ovarian HistoScanning Clinical Study Group,
Référence European radiology, 20, 8, page (1822-1830)
Publication Publié, 2010-08

Article révisé par les pairs

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Titre:	A new computer-aided diagnostic tool for non-invasive characterisation of malignant ovarian masses: results of a multicentre validation study.
Auteur:	Lucidarme, Olivier; Akakpo, Jean-Paul; Granberg, Seth; Sideri, Mario; Levavi, Hanoch; Schneider, Achim; Autier, Philippe; Nir, Dror; Bleiberg, Harry; Ovarian HistoScanning Clinical Study Group,
Informations sur la publication:	European radiology, 20, 8, page (1822-1830)
Statut de publication:	Publié, 2010-08
Sujet CREF:	Cancérologie
Mots-clés:	Ovarian cancer diagnosis
	Ovarian HistoScanning
	Tissue characterisation
	Ultrasound
MeSH keywords:	Adolescent
	Adult
	Aged
	Aged, 80 and over
	Algorithms
	Artificial Intelligence
	Europe
	Female
	Humans
	Image Enhancement -- methods
	Image Interpretation, Computer-Assisted -- methods
	Imaging, Three-Dimensional -- methods
	Middle Aged
	Ovarian Neoplasms -- ultrasonography
	Pattern Recognition, Automated -- methods
	Reproducibility of Results
	Sensitivity and Specificity
	Software
	Software Validation
	Ultrasonography, Doppler -- methods
	Young Adult
Note générale:	Evaluation Studies
	Journal Article
	Multicenter Study
	Validation Studies
	SCOPUS: ar.j
Langue:	Anglais
Identificateurs:	urn:issn:0938-7994
	info:doi/10.1007/s00330-010-1750-6
	info:scp/77957939537
	info:pmid/20306081