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Danielle Graveron-Demilly

Researcher at Claude Bernard University Lyon 1

Publications -  99
Citations -  3562

Danielle Graveron-Demilly is an academic researcher from Claude Bernard University Lyon 1. The author has contributed to research in topics: Iterative reconstruction & Artificial neural network. The author has an hindex of 20, co-authored 99 publications receiving 3347 citations. Previous affiliations of Danielle Graveron-Demilly include Institut national des sciences Appliquées de Lyon & University of Lyon.

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Java-based graphical user interface for the MRUI quantitation package

A. Naressi, +6 more
- 01 May 2001 - 
TL;DR: This article describes the Java-based version of the magnetic resonance user interface (MRUI) quantitation package, and shows that the Java programming language is very well suited for developing highly interactive graphical software applications such as the MRUI software.
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Java-based graphical user interface for MRUI, a software package for quantitation of in vivo/medical magnetic resonance spectroscopy signals

A. Naressi, +4 more
- 01 Jul 2001 - 
TL;DR: A Java-based graphical user interface for the magnetic resonance user interface (MRUI) quantitation package is described, which allows MR spectroscopists to easily perform time-domain analysis of in vivo/medical MR Spectroscopy data.
Journal ArticleDOI

Quantitation of magnetic resonance spectroscopy signals: The jMRUI software package

D. Stefan, +11 more
- 04 Sep 2009 - 
TL;DR: The quantum-mechanical simulator based on NMR-SCOPE, the quantitation algorithm QUEST and the main MRSI functionalities are described and Quantitation results of signals obtained in vivo from a mouse and a human brain are given.
Journal ArticleDOI

Cramér–Rao bounds: an evaluation tool for quantitation

Sophie Cavassila, +5 more
- 01 Jun 2001 - 
TL;DR: The influence of constraints (chemical prior knowledge) on spectral parameters of the peaks of doublets is demonstrated and the inherent benefits for quantitation are shown.
Journal ArticleDOI

Time-domain semi-parametric estimation based on a metabolite basis set.

Hélène Ratiney, +6 more
- 01 Feb 2005 - 
TL;DR: Three novel semi‐parametric approaches to handle 1H short echo‐time signals in terms of bias‐variance trade‐off are proposed and tested and valuable insight about quantitation precision is obtained from the correlation matrices.