Leentje Vanhamme

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We introduce AMARES (advanced method for accurate, robust, Noninteractive methods exist that are noniterative and and efficient spectral fitting) , an improved method for accurately computationally efficient and which can be fully automatic. and efficiently estimating the parameters of noisy magnetic resoA serious drawback however is the fact that only very(More)
Magnetic resonance spectroscopy (MRS) has been shown to be a potentially important medical diagnostic tool. The success of MRS depends on the quantitative data analysis, i.e., the interpretation of the signal in terms of relevant physical parameters, such as frequencies, decay constants, and amplitudes. A variety of time-domain algorithms to extract(More)
This paper describes a new quantitation method called AQSES for short echo time magnetic resonance spectra. This method is embedded in a software package available online from www.esat.kuleuven.be/sista/members/biomed/new/ with a graphical user interface, under an open source license, which means that the source code is freely available and easy to adapt to(More)
The purpose was to objectively compare the application of several techniques and the use of several input features for brain tumour classification using Magnetic Resonance Spectroscopy (MRS). Short echo time 1H MRS signals from patients with glioblastomas (n = 87), meningiomas (n = 57), metastases (n = 39), and astrocytomas grade II (n = 22) were provided(More)
Quantification of individual magnetic resonance spectroscopy (MRS) signals is possible in the time domain using interactive nonlinear least-squares fitting methods which provide maximum likelihood parameter estimates under certain assumptions or using fully automatic, but statistically suboptimal, black-box methods. In kinetic experiments time series of(More)
In this article an overview of time-domain quantitation methods is given. Advantages of processing the data in the measurement domain are discussed. The basic underlying principles of the methods are outlined and from them the situations under which these algorithms perform well are derived. Also an overview of methods to preprocess the data is given. In(More)
Accurate quantitation of Magnetic Resonance Spectroscopy (MRS) signals is an essential step before converting the estimated signal parameters, such as frequencies, damping factors, and amplitudes, into biochemical quantities (concentration, pH). Several subspace-based parameter estimators have been developed for this task, which are efficient and accurate(More)
A scheme for accurate quantification of (1)H spectra is presented. The method uses maximum-phase finite impulse response (FIR) filters for solvent suppression and an iterative nonlinear least-squares (NLLS) algorithm for parameter estimation. The estimation algorithm takes the filter influence on the metabolites of interest into account and can thereby(More)
In several applications of NMR spectroscopy the user is interested only in the components lying in a small frequency band of the spectrum. A frequency selective analysis deals precisely with this kind of NMR spectroscopy: parameter estimation of only those spectroscopic components that lie in a preselected frequency band of the NMR data spectrum, with as(More)