Intelligent Data Acquisition and Processing Methods for Multi-dimensional Magnetic Resonance Imaging of Cardiovascular Anatomy and Function with Minimal User Interaction.

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Research unit

INNOSUISSE

Project number

8005.3;7 LSPP-LS

Project title

Intelligent Data Acquisition and Processing Methods for Multi-dimensional Magnetic Resonance Imaging of Cardiovascular Anatomy and Function with Minimal User Interaction.

Texts for this project

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Short description	-	-	-
Abstract	-	-	-

Inserted texts

Category	Text
Short description (English)	Intelligent Data Acquisition and Processing Methods for Robust and Comprehensive Magnetic Resonance Imaging of Cardiac Anatomy and Function with Minimal User Interaction.
Abstract (English)	Development of adaptable coil array technology, self-adaptive data acquisition and post-processing methods for comprehensive and robust Magnetic Resonance imaging of the cardiovascular system. Methodological advances envisaged will facilitate time-resolved, truly volumetric coverage of both anatomy and function with high efficiency, during free breathing of the patient and with minimal user interaction. Dedicated post-processing and visualization techniques will be designed to interrogate multi-dimensional data sets and to allow extracting the relevant diagnostic parameters.

Category

Text

Short description
(English)

Intelligent Data Acquisition and Processing Methods for Robust and Comprehensive Magnetic Resonance Imaging of Cardiac Anatomy and Function with Minimal User Interaction.

Abstract
(English)

Development of adaptable coil array technology, self-adaptive data acquisition and post-processing methods for comprehensive and robust Magnetic Resonance imaging of the cardiovascular system. Methodological advances envisaged will facilitate time-resolved, truly volumetric coverage of both anatomy and function with high efficiency, during free breathing of the patient and with minimal user interaction. Dedicated post-processing and visualization techniques will be designed to interrogate multi-dimensional data sets and to allow extracting the relevant diagnostic parameters.