Software approaches for automated segmentation in dynamic contrast-enhanced ultrasound imaging

Fonte Standard Gras
Identifiant

Unité de recherche

INNOSUISSE

Numéro de projet

13741.1;13 PFFLE-LS

Titre du projet

Software approaches for automated segmentation in dynamic contrast-enhanced ultrasound imaging

Titre du projet anglais

Software approaches for automated segmentation in dynamic contrast-enhanced ultrasound imaging

Textes relatifs à ce projet

	Allemand	Français	Italien	Anglais
Description succincte	-	-	-
Résumé des résultats (Abstract)	-	-	-

Textes saisis

Catégorie	Texte
Description succincte (Anglais)	Software approaches for automated segmentation in dynamic contrast-enhanced ultrasound imaging
Résumé des résultats (Abstract) (Anglais)	Ultrasound (US) is a major imaging modality for image-guided therapy and diagnosis in medicine. Today, there is a need for robust, accurate and efficient automated segmentation methods for biological structures (organs and focal diseases) within US imaging systems. In this project we will first develop a semisupervised segmentation framework for contrast enhanced US (CEUS) imaging. Secondly, its implementation in Bracco¿s software will add significant value to the current imaging process by providing more accurate and automated quantitave analysis of the image.

Catégorie

Texte

Description succincte
(Anglais)

Software approaches for automated segmentation in dynamic contrast-enhanced ultrasound imaging

Résumé des résultats (Abstract)
(Anglais)

Ultrasound (US) is a major imaging modality for image-guided therapy and diagnosis in medicine. Today, there is a need for robust, accurate and efficient automated segmentation methods for biological structures (organs and focal diseases) within US imaging systems. In this project we will first develop a semisupervised segmentation framework for contrast enhanced US (CEUS) imaging. Secondly, its implementation in Bracco¿s software will add significant value to the current imaging process by providing more accurate and automated quantitave analysis of the image.