Research team

Expertise

Arjan den Dekker’s research focuses on new developments in the domain of model-based measurement, aiming at quantitative measurements of physical parameters with the highest attainable accuracy and precision. Main areas of application: quantitative magnetic resonance imaging and quantitative electron microscopy.

Breakthroughs in Quantitative Magnetic resonance ImagiNg for improved Detection of brain Diseases (B-Q MINDED). 01/01/2018 - 31/03/2022

Abstract

Magnetic resonance imaging (MRI) is one of the most useful and rapidly growing neuroimaging tools. Unfortunately, signal intensities in conventional MRI images are expressed in relative units that depend on scanner hardware and acquisition protocols. While this does not hinder visual inspection of anatomy, it hampers quantitative comparison of tissue properties within a scan, between successive scans, and between subjects. In contrast, advanced quantitative MRI (Q-MRI) methods like MR relaxometry or diffusion MRI do enable absolute quantification of biophysical tissue characteristics. Evidence is growing that Q-MRI techniques detect subtle microscopic damage, enabling more accurate and early diagnosis of neurodegenerative diseases. However, due to the long scan time required for Q-MRI, causing discomfort for patients and limiting the throughput, Q-MRI methods have not entered clinical practice yet. B-Q MINDED aims to overcome the current barriers by developing widely-applicable post-processing breakthroughs for accelerating Q-MRI. The originality of B-Q MINDED lies in its ambition to replace the conventional rigid multi-step processing pipeline with an integrated single-step parameter estimation framework. This approach will unlock a wealth of options for optimization of Q-MRI. To accomplish this goal, B-Q MINDED proposes a collaborative cross-disciplinary approach (from basic MR physics to clinical applications) with strong involvement of industry.

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Project type(s)

  • Research Project

A superresolution framework for quantitative brain perfusion map estimation using Arterial Spin Labelling 01/01/2016 - 31/12/2019

Abstract

Perfusion magnetic resonance imaging (MRI) is an imaging tool to assess the spatial distribution of microvascular blood flow. Many neurological disorders are accompanied by cerebral blood flow (CBF) alterations, which makes perfusion MRI indispensable in routine clinical practice. Arterial spin labeling (ASL) perfusion MRI uses magnetically labeled arterial blood water as an endogenous diffusible tracer. Tissue perfusion is measured from the signal difference between images with labeled blood and control images. Lack of ionizing radiation, complete non-invasiveness, and absolute quantification of perfusion parameters make ASL a unique perfusion imaging modality. Current ASL methods, however, suffer from problems such as noisy images and patient movement, which are inherent to the acquisition process. My project aims to develop a framework that incorporates new ASL acquisition and reconstruction methods targeting these problems simultaneously. The core of this framework revolves around super resolution reconstruction (SRR) ASL imaging which allows direct estimation of high-resolution perfusion parameters from a set of differently sampled low-resolution images. Results will yield a patient-friendly, cost-efficient and quantitative protocol that allows accurate and precise perfusion measurement at increased resolution in a clinically acceptable acquisition time, by that removing the main obstacles for ASL to become the golden standard for perfusion measurements.

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  • Research Project

A super-resolution framework for quantitative brain perfusion mapping with Arterial Spin Labeling. 01/10/2015 - 31/12/2015

Abstract

Perfusion magnetic resonance imaging (MRI) is an imaging tool to assess the spatial distribution of microvascular blood flow. Many neurological disorders are accompanied by cerebral blood flow (CBF) alterations, which makes perfusion MRI indispensable in routine clinical practice. Arterial spin labeling (ASL) perfusion MRI uses magnetically labeled arterial blood water as an endogenous diffusible tracer. Tissue perfusion is measured from the signal difference between images with labeled blood and control images. Lack of ionizing radiation, complete non-invasiveness, and absolute quantification of perfusion parameters make ASL a unique perfusion imaging modality. Current ASL methods, however, suffer from problems such as noisy images and patient movement, which are inherent to the acquisition process. My project aims to develop a framework that incorporates new ASL acquisition and reconstruction methods targeting these problems simultaneously. The core of this framework revolves around super-resolution reconstruction (SRR) ASL imaging which allows direct estimation of high-resolution perfusion parameters from a set of differently sampled low-resolution images. Results will yield a patient-friendly, cost-efficient and quantitative protocol that allows accurate and precise perfusion measurement at increased resolution in a clinically acceptable acquisition time, by that removing the main obstacles for ASL to become the golden standard for perfusion measurements.

Researcher(s)

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  • Research Project

Bringing light atoms to light: precise characterization of light-atom nanostructures using transmission electron microscopy. 01/01/2015 - 31/12/2018

Abstract

The aim of this project is to detect extremely light atoms, to determine their atom types and to measure their positions down to picometer precision. Therefore, aberration corrected scanning transmission electron microscopy will be combined with innovative quantitative measuring.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project