English

Felix Lucka

Volledige naam
Dr. F. Lucka
E-mail
Felix.Lucka@cwi.nl
Telefoon
+31 20 592 4071
Kamer
L020a
Afdeling(en)
Computational Imaging
Functie(s)
Scientific Staff Member
Startpagina
http://felixlucka.github.io/
Felix Lucka

Biography

I'm interested in mathematical challenges arising from biomedical imaging applications that have a classical inverse problem described by partial differential equations at their core. As such, my work draws from various fields of applied mathematics, including Bayesian inference, variational regularization, compressed sensing, computational optimization, deep learning and numerical analysis. The main applications I currently work on are computed tomography (CT), photoacoustic tomography (PAT), ultrasound tomography (UST), electro- and magnetoencephalography (EEG/MEG) and magnetic resonance imaging (MRI ). After a first degree in mathematics and physics in 2011, I studied for a PhD in applied mathematics in WWU Münster (Germany), which included a research visit at UCLA. From September 2014 to October 2017, I worked as a postdoc at UCL, after which I joined CWI as a tenure track researcher.

Publications

All publications

Professional activities

  • Speaker: "Sparse Bayesian Inference & Uncertainty Quantication for Inverse Imaging Problems", Statistics for Structures Seminar, University of Leiden
  • Organizer: Minisymposium "Imaging with Light and Sound", SIAM Imaging Science, Bologna (2018)
  • Speaker: "Variational Models for Dynamic Tomography", Inverse Problems: Modeling and Simulation, Malta, May 21 - 25, 2018.
  • Speaker: "Hierarchical Bayesian Uncertainty Quantification for EEG/MEG Source Reconstruction", SIAM Conference on Imaging Science, Bologna
  • Speaker: "Challenges of Mathematical Image Reconstruction", Colloquium Mathematics, Groningen
  • Organizer: Minisymposium "Tomographic Imaging: Recent Advances, Exciting Applications and New Horizons", Applied Inverse Problems Conference, Grenoble (2019)
  • Organizer: Minisymposium "Deep Learning and Inverse Problems", ICIAM, Valencia (2019)
  • Organizer: MUMMERING Workshop on "Dynamic Imaging", Leiden (2019)
  • Speaker: "On Challenges in Quantitative Photoacoustic Tomography and Ultrasound Computed Tomography", Mathematical and Numerical Approaches for Multi-Wave Inverse Problems, Marseille
  • Speaker: "Challenges of Mathematical Image Reconstruction", DIAMANT symposium, Eindhoven
  • Speaker: "Deep Learning for Computed Tomography Applications", Applied Inverse Problems Conference, Grenoble
  • Speaker: "Computational and Practical Challenges of 4D Tomography Applications", Applied Inverse Problems Conference, Grenoble
  • Speaker: "New Applications and Challenges in X-Ray Tomography", ICIAM, Valencia
  • Speaker: "Hierarchical Bayesian Uncertainty Quantication for EEG/MEG Source Reconstruction", ICIAM, Valencia
  • Speaker: "4D Computed Tomography with Sequential Scanning Systems", IMA, London
  • Speaker: "Dynamic Image Reconstruction & Motion Estimation", MUMMERING Workshop on Dynamic Imaging, Leiden
  • Speaker: "Time-Domain Full Waveform Inversion for High Resolution 3D Ultrasound Computed Tomography of the Breast", International Workshop on Medical Ultrasound Tomography, Detroit
  • Speaker: "Image Reconstruction: A Playground for Curious Applied Mathematicians", CWI Scientific Meetings , Amsterdam
  • Speaker: "Image Reconstruction: A Playground for Applied Mathematicians", Partial differential equations and applications seminar, TU Delft
  • Speaker: "Imaging the Acoustic and Optical Properties of the Breast with USCT and PAT", SIAM Imaging Science
  • Speaker: "Joint Tomographic Image Reconstruction and Motion Estimation", SIAM Imaging Science
  • Organizer: Dutch Inverse Problems Meeting (2021)
  • Speaker: "Simultaneous Tomographic Image Reconstruction and Motion Estimation", UGCT Seminar, Feb 23, 2021.
  • Speaker: "Computational Challenges in Photoacoustic and Ultrasonic Breast Imaging", Excalibur SLE Workshop, May 07, 2021.
  • Speaker: "Deep Learning in Computational Imaging", MaLGA Seminar Series
  • Organizer: Dutch Inverse Problems Meeting (2022)
  • Organizer: FleX-ray Lab 5 Years Anniversary Symposium (2022)
  • Speaker: "Computational and Experimental Challenges of 3D Ultrasound Tomography", Conference on Mathematics of Wave Phenomena”, KIT
  • Speaker: "Image Reconstruction - A Playground for Applied Mathematicians", Applied Analysis Seminar, Radboud University
  • Speaker: "Photoacoustic and Ultrasonic Tomography for Breast Imaging", SIAM Imaging Science conference
  • Speaker: "Photoacoustic & Ultrasonic Tomography for Breast Cancer Imaging", 3rd IMA Conference on Inverse Problems from Theory to Application, Edinburgh
  • Speaker: "Deep Learning in Computational Imaging", AI & Mathematics Workshop, Amsterdam
  • Speaker: "Ultrasonic Breast Tomography via 3D Full Waveform Inversion", Department of Imaging Physics, TU Delft
  • Speaker: "Photoacoustic and Ultrasonic Tomography for Breast Imaging", CWI Scientific Meetings, Amsterdam
  • Speaker: "Photoacoustic and Ultrasonic Tomography for Breast Imaging", INI workshop on Rich and non-linear tomography in medical imaging, materials and non destructive testing, Cambridge, UK.
  • Speaker: "Photoacoustic and Ultrasonic Tomography for Breast Imaging", Oberwolfach Workshop on Tomographic Inverse Problems: Mathematical Challenges and Novel Applications, Germany.
  • Speaker: "Learning for X-ray Computed Tomography", INdAM workshop on Learning for Inverse Problems, Rome, Italy
  • Speaker: "Photoacoustic and Ultrasonic Tomography for Breast Imaging" Applied Inverse Problems Conference, Götteningen, Germany
  • Organizer: Dutch Inverse Problems Meeting (2023)
  • Speaker: "Photoacoustic and Ultrasonic Tomography for Breast Imaging", Medical Physics Seminar at the MLU Halle-Wittenberg, Germany

Grants

  • NWO Vidi grant on Dynamic X-ray Computed Tomography using Deep Generative Networks (2024)
  • EC HORIZON TMA MSCA grant on Computational Imaging as a Training Network for Smart Biomedical Devices (2023)
  • NWO KLEIN-I grant on Translation-Driven Development of Deep Learning for Simultanous Tomographic Image Reconstruction and Segmentation (2020)
  • PPP project with Applus RTD on Deep learning and compressed sensing for ultrasonic nondestructive testing (2019)

Current projects with external funding

  • COmputaNal Imaging as a training Network for Smart biomedical dEvices (CONcISE (101072354))
  • Dynamic X-ray Computed Tomography using Deep Generative Networks (None)
  • Translation-Driven Development of Deep Learning for Simultaneous Tomographic Image Reconstruction and Segmentation (None)

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