Current BEP/MEP projects:
Below is an overview of the current student projects. For more detailed information, please click on the respective button. If "your project" is not listed, please contact one of the below researchers directly to discuss the possibilities for a project on Medical Imaging.
Ultrasound is the most widely used diagnostic technique because of its versatility, ease of use, cost effectiveness, repeatability for patients and reproducibility. Until now the ultrasound diagnosis were based in 2D imaging,
but new developments with integrated electronics has open novel three-dimensional (3D) ultrasound imaging methods and systems for real-time imaging of heart, liver, kidney and other organs but also for monitoring the perfusion of the brains of preterm babies. If you like the combination of signal processing, computer simulations and experimental work and like to apply your work in the medical field than medical ultrasound imaging may just be something for you.
- Monitoring the perfusion of preterm babies
One in ten children is born prematurely, which amounts to approximately 500,000 preterm infants in Europe each year. Yet, they regularly show neurodevelopmental problems, including cognitive deficits, motor disabilities and psychiatric diseases with ensuing lifelong burdens for the up growing individuals and their families. A major cause of these neurodevelopmental problems is brain injury, linked to inadequate brain perfusion during and after delivery as shown in the figure (Two-dimensional perfusion map: Left, normal perfusion. Right, perfusion defect).
We pursue fundamental advances at the interface of ultrasound imaging physics and molecular engineering, taking advantage of the discovery of acoustic biomolecules to interface ultrasound waves with cellular processes. The resulting technologies will be applied in many areas of biology and medicine, and a primary focus of the lab is the non-invasive ultrasound assessment of vascular function at all scales, from arteries down to capillaries and cells.
The realization of novel imaging devices and techniques poses many challenges. For example, a matrix array for making 3D medical images contains thousands of piezoelectric elements that can each transmit and receive ultrasound pulses. To deal with this large amount of signals, the elements are directly mounted on an electronic chip that performs the first stage of data processing. Typical challenges are: minimization of crosstalk between the elements, development of beamforming strategies for superfast scanning of a volume, and the development of imaging strategies for achieving superior 3D resolution. Another part of my research involves accurate computation of acoustic waves, in particular non-linear waves that form the basis of medical harmonic imaging. Most projects involve both experimental and numerical work, and can have a component that will be performed at Erasmus MC.
- 3D intra-cardiac echography catheter
A real-time 3D ultrasound probe for intra-cardiac echography (ICE) could provide accurate guidance during minimally-invasive procedures for heart valve replacement and treatment of cardiac rhythm disorders. Currently, only two-dimensional visualization is possible. This project involves novel methods and techniques that will enable a real-time 3D ICE catheter. Rather than sequentially scanning the heart with a narrow steered ultrasound beam, the complete volume will be insonified in one shot by transmitting a non-steered, spherically expanding wave, originating from a virtual point source behind the array. This is much simpler and much faster than generating a focused beam. Our part of the project involves the design of the ultrasound array and the beamforming strategy.
Current ultrasound imaging techniques use only part of the information enclosed in the recorded high frequency sound waves limiting the quality of and information present in the image. Advanced ultrasound imaging methods, known as full waveform inversion, use all information enclosed in the recorded field - including multiple scattering and diffraction effects - to improve the image quality and to retrieve accurate quantitative information about the tissue parameters. In this research field, we develop and test new imaging and inversion methods using both synthetic and measured data. In close collaboration with Karlsruhe Institute of Technology (Germany) and Industrial University of Santander (Colombia) we apply those methods in particular to breast cancer detection.
- Reconstructing acoustic medium parameters from scattered wave fields
An acoustic field is sensitive to spatial variations in the acoustic medium parameters (sound speed, density and attenuation). Reconstructing these parameters from the recorded field makes it feasible to differentiate a benign from malignant tumour. Up to date, most people are only reconstructing speed of sound profiles, however … if you like programming and are not afraid of mathematics, it might be a challenging project for you to reconstruct all the parameters from the measured scattered wave field. If interested, part of this project can be carried out in the beautiful city Bucaramanga, at the Industrial University of Santander (Colombia)!
My research focuses on medical image analysis. I aim to develop new techniques to measure relevant features from medical images (e.g. MRI/CT). These analysis techniques are characterized by clever modelling, incorporating prior knowledge and relying strongly on the physical principles of the image formation. If you like to solve a real clinical problem using fundamental theory than you are very welcome to join my group!
- Diffusion MRI of the Brain
Diffusion MRI allows to determine the integrity of white matter tracts, based on diffusion measurements. This is highly relevant for study diseases such as ALS and Alzheimer’s disease.
- Dynamic Contrast MRI in the Abdomen
Dynamic contrast enhanced MRI enables measurent of properties of the vasculature in patients. This is important for characterization of pathologies such as Crohn's disease and liver tumors. Previously students have worked on techniques to align imaging data from different patients, modalities and over time, to model diffusional processes and analyze differences between distinct patient groups. When you drop by, then I will inform you about our latest issues we have!
At Mars Lab we work all day and night - mostly day - to advance quantitative Magnetic Resonance Imaging (MRI). We pursue two main veins of research. Firstly, we work on the development of novel biomarkers to enable non-invasive assessment of tissue integrity in greater detail and provide insights beyond conventional MRI contrasts. Secondly, we work on accelerated and motion-insensitive quantification of imaging parameters to facilitate clinical translation of quantitative MRI.
- Audio source separation for Magnetic Resonance Imaging (MRI) acoustic noise components
MRI is a very powerful and non-invasive technique for medical imaging. However, most patients get annoyed or even scared, only because MRI can be very loud during scans (louder than a jet engine!). The main source of this noise comes from vibrating gradient coils - they are affected by the Lorentz force as the currents in them are rapidly switched. In addition, there are other noise sources in the imaging room, such as helium pump and air handling equipment.
To understand the MRI acoustic noise better, in this project we will use spatial source separation to decompose the noise signal into its main components. This will enable studying the noise caused by the gradient currents directly, and eventually lead to developing quieter MRI.
- Disentangling the Brain’s Chatter - Identifying single neurons from electrophysiological recordings
Electrophysiological recordings are the backbone of neuroscience, enabling to listen to the electrical signals that constitute our brain activity at a single cell resolution. Novel hardware developments put ephys-recordings at a brink of revolution, enabling the simultaneous recording from hundreds of neurons rather than less than 10. These developments stir up neuroscience as they potentially enable the detailed understanding of neural circuits by listening to each individual neuron.