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
History
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
MSc students
- Teodor Licurici
- Koen Rodewijk
- Janine Hendriks
- Corne Haasjes
- Celine Schaus
- Ilja Venema
- Renjie Dai
- Pierre-Antoine Denarié
- Enpu Chen
- Cesar Eduardo Cornejo Ramirez
- Aggariyo Wanagiri
- Yanan Hu
- Nan Lin
- Yitong Tao
- Ruben Wijnands
- Jinchen Zeng
- Xiaoning Shi
- Chuhan Wang
- Jordi de Vries
- Cees Kos
- Haoran Bi
- Aleid Bekkering
- William Hunter
- Thomas Roos
- Yingfeng Jiang
Alumni
- Tijs Moree (2022)
- Pallas Koers (2022)
- Michiel Van Hoeven (2022)
- Arthur Kordes (2021)
- Arda Kaygan (2021)
- Gaia Zin (2021)
- Jeroen Roest (2021)
- Eris van Twist (2021)
- Sarthak Agarwal (2021)
- Karen van der Werff (2021)
- Preetha Vijayan (2021)
- Maarten Enthoven (2021)
- Bas Liesker (2021)
- Leonie Pereboom (2021)
- Javier Guinea Perez (2021)
- Prernna Bhatnagar (2020)
- Kriti Dhingra (2020)
- Yuchen Yin (2020)
- Sonnya Dellarosa (2020)
- Alejandro Monreal (2020)
- Maria Macarulla Rodriguez (2020)
- Manojna Vedula (2020)
- Joris Belier (2019)
- Mandani (Mado) Ntekouli (2019)
- Rajesh Rajwade (2019)
- Bart Kölling (2019)
- Chenhong Ji (2019)
- Sherine Brahma (2019)
- Xin An (2019)
- Bram Visser (2019)
- Pranav Prakash (2019)
- Yiting Lu (2019)
- Bart de Vos (2019)
- Juriaan Van der Graaf (2019)
- Bastian Generowicz (2019)
- Zheheng Liu (2019)
- Yuyang Wang (2018)
- Jack Tchimino (2018)
- Feng Ma (2018)
- Lars Rehbein (2018)
- Haidong Hao (2018)
- Dirk Schut (2018)
- Makrina Sekeri (2018)
- Xuyang Li (2017)
- Jelimo Maswan (2017)
- Jiying Dai (2017)
- Peter Stijnman (2017)
- Tariq Saboerali (2016)
- Joost van der Kemp (2016)
- Reijer Leijsen (2016)
- Michiel Gerlach (2016)
- Andrejs Fedjajevs (2016)
- Pim van der Meulen (2016)
- Patrick Fuchs (2016)
- Marina Nano (2015)
- Vana Panagiotou (2015)
- Di Feng (2015)
- Jorn Zimmerling (2014)
- Jason Mensingh (2013)
- Viktor Stoev (2013)
- Jeroen van Gemert (2013)
- Michiel van Hoeven (-0001)