Parameter Estimation Applied to Medical and Biological Sciences

Dit vak wordt in het Engels aangeboden. Omschrijvingen kunnen daardoor mogelijk alleen in het Engels worden weergegeven.

Doel vak

The course treats the theory of parameter estimation problems in
general, but the theory is illustrated extensively by examples from
medical and biological sciences and brain imaging (fMRI and MEG/EEG) in
particular. Linear and non-linear regression analysis is treated, as
well as confidence intervals and significance testing. The goal of the
course is to provide insight into the theory of parameter estimation and
to develop a critical attitude towards its application and
interpretation in order to avoid inconsistent and improper use of the

Inhoud vak

Linear-non linear parameter models, basic matrix-vector algebra,maximum
likelihood principle, correlated-uncorrelated noise, OLS, GLS, data
outliers, nuisance parameters, linear (time invariant) filters,
projection filters t-test, F-test, confidence intervals, multiple
testing, fMRI data model, missing data, MEG/EEG source localisation.
These topics are treated in the form of a series of lectures alternated
with exercises.

Extra topics: L1 en L2 norms.


Lecture and optional (MatLab) exercises.


Written exam plus bonus point for critical review of scientific paper.

Vereiste voorkennis

In order to participate in this course, students are required to have
successfully completed Image Processing for MNS (X_422612) and Medical
Imaging for MNS (XM_0063).


A syllabus and slides will be provided by the lecturer.



Aanbevolen voorkennis

Basic Matlab experience is recommended to enable completion of optional
Matlab exercises.

Algemene informatie

Vakcode X_432631
Studiepunten 6 EC
Periode P4
Vakniveau 500
Onderwijstaal Engels
Faculteit Faculteit der Bètawetenschappen
Vakcoördinator dr. I.H.M. van Stokkum
Examinator dr. J.C. de Munck
Docenten dr. J.C. de Munck
dr. I.H.M. van Stokkum

Praktische informatie

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