Biomedical signal processing/wavefield imaging

Contact: Rob Remis

  • Signal processing and imaging (estimation and detection for diagnostics and therapy), in particular Magnetic Resonance Imaging (MRI) from EM modeling and instrument design to signal processing, image formation (numerical inversion techniques) and tissue parameter estimation, with applications to medical diagnostics in collaborations with university hospitals.
  • Biomedical signals estimation and detection: Estimation of signal parameters from multichannel signals (e.g. ECG); detection and localization of medical conditions such as heart fibrillation, epilepsy.

Projects under this theme

Prostate cancer detection using ultrasound

Tensor techniques to improve the analysis of (3D+time) ultrasound images

Delft Tensor AI Lab

Tensor-based AI methods for biomedical signals

Three-dimensional Ultrasound Imaging Through Compressive Spatial Coding

Develop smart compressive coding masks to make 3D ultrasound imaging cheap and widely applicable.

Multimodal, multiresolution brain imaging

Developing a novel brain imaging paradigm combining functional ultrasound and EEG

Medical Delta Cardiac Arrhythmia Lab

Part of a larger program (with Erasmus MC) to unravel and target electropathology related to atrial arrhythmia

A Sustainable MRI System to Diagnose Hydrocephalus in Developing Countries

Development of a low-cost MRI scanner including processing to diagnose hydrocephalus

Earlier recognition of cardiovascular diseases

Atrial Fibrillation FIngerPrinting: Spotting Bio-Electrical Markers to Early Recognize Atrial Fibrillation by the Use of a Bottom-Up Approach

Good Vibrations - Fast and Robust Wave Field Computations in Complex Structures Using Krylov Resonance Expansions

Using Krylov subspace reduction techniques to solve wave field problems in complex media (resonanting nano-scale devices and seismic exploration)


Dielectric enhanced MRI

Modeling and analyzing the effect of high permittivity pads in MRI imaging