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Development of biostochastic methods for analysis of spatio-temporal signals – with applications to muscle physiology and cancer tumor biology

Research project The aim of this project is to develop stochastic models and statistical methods to provide more reliable estimation of the physiological parameters which can be obtained from different spatio-temporal signals.

With modern inverstigations spatio-temporal signals can be received from many different measurements. Directed application areas are Magnetic Resonance Imaging (MRI), where both dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and magnetic resonance spectroscopy (MRS) can be used, and Muscle Physiological studies, where multi-channel eletromyography (MC-EMG), ultrasound, and near infrared (NIR) will be integrated. Methods will be applied to muscle physiology and characterization of cancer tumor. However, the focus will be on the developments of biostochastic methods. The biostochastic methods developed in this project shall describe relevant parameters quantitatively with determined uncertainty estimation. In order to minimize the uncertainty in the parameter estimators it is necessary to reduce the noise in the signals. This requires also innovation of methodology. Therefore methods for noise reduction will also be developed and evaluated.

Head of project

Jun Yu
Professor
E-mail
Email

Project overview

Project period:

2008-08-01 2011-06-30

Funding

Finansår , 2008, 2009, 2010, 2011

huvudman: Jun Yu, finansiar: EU Regional Development Fund, y2008: 250, y2009: 500, y2010: 500, y2011: 250,

Participating departments and units at Umeå University

Department of Mathematics and Mathematical Statistics, Faculty of Science and Technology

Research area

Medical technology, Statistics

Project description

The aim of this project is to develop stochastic models and statistical methods to provide more reliable estimation of the physiological parameters which can be obtained from different spatio-temporal signals.

With modern inverstigations spatio-temporal signals can be received from many different measurements. Directed application areas are Magnetic Resonance Imaging (MRI), where both dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and magnetic resonance spectroscopy (MRS) can be used, and Muscle Physiological studies, where multi-channel eletromyography (MC-EMG), ultrasound, and near infrared (NIR) will be integrated. Methods will be applied to muscle physiology and characterization of cancer tumor. However, the focus will be on the developments of biostochastic methods.

The biostochastic methods developed in this project shall describe relevant parameters quantitatively with determined uncertainty estimation. In order to minimize the uncertainty in the parameter estimators it is necessary to reduce the noise in the signals. This requires also innovation of methodology. Therefore methods for noise reduction will also be developed and evaluated.

This project has a strong connection to the projects ”Adaptive image-optimized cancer treatment – development of MRI methods” (Prof. Mikael Karlsson, Radiation Physics, Umeå University Hospital) and ”Development of multimodal methods for increasing understanding of changes and deseases in the muscular skeletal system” (Prof. Stefan Karlsson, Biomedical Engineering, Umeå University Hospital).