Biomedical Physics

Course with Participations of Group Members

Offers for Theses in the Group

Application of diffusion models to sparse-view CT

suitable as

• Master’s Thesis Biomedical Engineering and Medical Physics

Supervisor: Franz Pfeiffer

Characterisation of photon-counting hybrid-pixel detectors

Hybrid-pixel photon-counting detectors have been developed in high-energy physics in the past and presently being implemented in several medical imaging applications. They offer higher spatial resolution and additional energy resolution and therefore hold significant potential for future improvement in radiography and CT. This work will investigate some basic detector physics characteristics, and specifically investigate the response of such detectors to inclined radiation, which is very important for some spectral imaging applications. The project will be carried out in close collaboration with external industrial collaborators. Character of thesis work: experimental physics (70%) & image processing (30%) For more information, please contact: Daniel Berthe (daniel.berthe@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Biomedical Engineering and Medical Physics

Supervisor: Franz Pfeiffer

Characterisation of photon-counting hybrid-pixel detectors

Hybrid-pixel photon-counting detectors have been developed in high-energy physics in the past and presently being implemented in several medical imaging applications. They offer higher spatial resolution and additional energy resolution and therefore hold significant potential for future improvement in radiography and CT. This work will investigate some basic detector physics characteristics, and specifically investigate the response of such detectors to inclined radiation, which is very important for some spectral imaging applications.

The project will be carried out in close collaboration with external industrial collaborators.

Character of thesis work: experimental physics (70%) & image processing (30%)

For more information, please contact: Daniel Berthe (daniel.berthe@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Applied and Engineering Physics

Supervisor: Franz Pfeiffer

Distortion correction for high-resolution quantitative X-ray imaging detectors

X-ray imaging detectors - in particular for high-resolution microscopy applications - may suffer from distortions, which degrade the image quality. This can have severe negative effects for quantitative applications, such as 3D micro-computed tomography. This project focuses on the characterisation of distortions of several X-ray imaging detectors at the Munich Compact Light Source, and the subsequent development of suitable correction methods.

Character of thesis work: mainly computational (image processing)  

For more information, please contact: Martin Dierolf (martin.dierolf@tum.de), Johannes Melcher (johannes.melcher@tum.de), or Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Applied and Engineering Physics

Supervisor: Franz Pfeiffer

Distortion correction for high-resolution quantitative X-ray imaging detectors

X-ray imaging detectors - in particular for high-resolution microscopy applications - may suffer from distortions, which degrade the image quality. This can have severe negative effects for quantitative applications, such as 3D micro-computed tomography. This project focuses on the characterisation of distortions of several X-ray imaging detectors at the Munich Compact Light Source, and the subsequent development of suitable correction methods.

Character of thesis work: mainly computational (image processing)  

For more information, please contact: Martin Dierolf (martin.dierolf@tum.de), Johannes Melcher (johannes.melcher@tum.de), or Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Biomedical Engineering and Medical Physics

Supervisor: Franz Pfeiffer

Estimation of Compton scattering in X-ray imaging using neural networks

Compton scattering is one of the two primary interactions of X-rays with matter in X-ray imaging (next to photoelectric absorption). In contrast to photoelectric absorption, Compton scattering is an inelastic scattering process during which X-ray photons are deflected and transfer some of their energy to the interaction partner, typically an electron. As a consequence, photons may still reach the detector after Compton interaction. In X-ray imaging, this leads to a smoothly varying background, which reduces contrast and is detrimental to quantitative imaging. Furthermore, the Compton scatter background is not uniform, but instead depends on the materials and their distribution within an imaged object. This makes a straight-forward analytical correction difficult, and existing tools to estimate the Compton background are limited in their accuracy and applicability.

 

The goal of this thesis is to develop methods to a) estimate the Compton scattering background from simple radiographs, and b) correct these images for it. This will be done using machine learning, in particular convolutional neural networks. The student will generate Monte-Carlo simulations based on the Geant4 platform, design and train neural networks, apply them for Compton scatter correction on clinical radiography images, and compare the results to existing approaches.

 

The project involves mostly data preparation, and computational work (85%, primarily Python, with potentially some C++ for Geant4), as well as experimental data collection (15%). The project will involve collaboration with the Radiology department at the TUM Hospital Klinikum rechts der Isar.

 

Basic experience in scientific programming, Monte-Carlo simulations, neural networks, and/or X-ray imaging are desirable.

 

For more information, please contact: Dr. Florian Schaff (florian.schaff@tum.de), or Prof. Franz Pfeiffer (franz.pfeiffer@tum.de).

suitable as

• Master’s Thesis Biomedical Engineering and Medical Physics

Supervisor: Franz Pfeiffer

Estimation of Compton scattering in X-ray imaging using neural networks

Compton scattering is one of the two primary interactions of X-rays with matter in X-ray imaging (next to photoelectric absorption). In contrast to photoelectric absorption, Compton scattering is an inelastic scattering process during which X-ray photons are deflected and transfer some of their energy to the interaction partner, typically an electron. As a consequence, photons may still reach the detector after Compton interaction. In X-ray imaging, this leads to a smoothly varying background, which reduces contrast and is detrimental to quantitative imaging. Furthermore, the Compton scatter background is not uniform, but instead depends on the materials and their distribution within an imaged object. This makes a straight-forward analytical correction difficult, and existing tools to estimate the Compton background are limited in their accuracy and applicability.

 

The goal of this thesis is to develop methods to a) estimate the Compton scattering background from simple radiographs, and b) correct these images for it. This will be done using machine learning, in particular convolutional neural networks. The student will generate Monte-Carlo simulations based on the Geant4 platform, design and train neural networks, apply them for Compton scatter correction on clinical radiography images, and compare the results to existing approaches.

 

The project involves mostly data preparation, and computational work (85%, primarily Python, with potentially some C++ for Geant4), as well as experimental data collection (15%). The project will involve collaboration with the Radiology department at the TUM Hospital Klinikum rechts der Isar.

 

Basic experience in scientific programming, Monte-Carlo simulations, neural networks, and/or X-ray imaging are desirable.

 

For more information, please contact: Dr. Florian Schaff (florian.schaff@tum.de), or Prof. Franz Pfeiffer (franz.pfeiffer@tum.de).

suitable as

• Master’s Thesis Applied and Engineering Physics

Supervisor: Franz Pfeiffer

Evaluation of spectral photon-counting detectors for chest X-ray cancer screening

This project will explore the use of latest hybrid-pixel photon-counting detectors for improving the diagnostic accuracy of chest X-ray examinations. More specifically, this work will use dedicated lung phantoms for evaluationg the potential clinical benefit of the enhanced spatial resolution and energy-resolving capabilities of latest photon-countinghybrid pixel detectors for lung cancer screening. The project will be carried out in close collaboration with the Department of Radiology at the TUM Klinikum Rechts der Isar and with an external industrial collaborator located in the Munich area.

Character of thesis work: experimental physics (50%) & image processing (50%)

For more information, please contact: Daniel Berthe (daniel.berthe@tum.de), Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Biomedical Engineering and Medical Physics

Supervisor: Franz Pfeiffer

Evaluation of spectral photon-counting detectors for chest X-ray cancer screening

This project will explore the use of latest hybrid-pixel photon-counting detectors for improving the diagnostic accuracy of chest X-ray examinations. More specifically, this work will use dedicated lung phantoms for evaluationg the potential clinical benefit of the enhanced spatial resolution and energy-resolving capabilities of latest photon-countinghybrid pixel detectors for lung cancer screening. The project will be carried out in close collaboration with the Department of Radiology at the TUM Klinikum Rechts der Isar and with an external industrial collaborator located in the Munich area.

Character of thesis work: experimental physics (50%) & image processing (50%)

For more information, please contact: Daniel Berthe (daniel.berthe@tum.de), Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Applied and Engineering Physics

Supervisor: Franz Pfeiffer

Evaluation of spectral photon-counting detectors for improved 3D cone-beam dental CT imaging applications

This project will explore the use of latest hybrid-pixel photon-counting detectors for improving the image quality in 3D (cone-beam CT) dental imaging applications. More specifically, the project aims at the experimental evaluation of the potential benefits of applying spectral material decomposition for dental CT application. The work will include preclinical experiments using dedicated anthropomorphic head phantoms and subsequent image analysis and interpretation. The project will be carried out in close collaboration with the Department of Radiology at the TUM Klinikum Rechts der Isar and with an external industrial collaborator located in the Munich area.

Character of thesis work: experimental physics (30%) & image processing (70%)

For more information, please contact: Daniel Berthe (daniel.berthe@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Biomedical Engineering and Medical Physics

Supervisor: Franz Pfeiffer

Evaluation of spectral photon-counting detectors for improved 3D cone-beam dental CT imaging applications

This project will explore the use of latest hybrid-pixel photon-counting detectors for improving the image quality in 3D (cone-beam CT) dental imaging applications. More specifically, the project aims at the experimental evaluation of the potential benefits of applying spectral material decomposition for dental CT application. The work will include preclinical experiments using dedicated anthropomorphic head phantoms and subsequent image analysis and interpretation. The project will be carried out in close collaboration with the Department of Radiology at the TUM Klinikum Rechts der Isar and with an external industrial collaborator located in the Munich area.

Character of thesis work: experimental physics (30%) & image processing (70%)

For more information, please contact: Daniel Berthe (daniel.berthe@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Applied and Engineering Physics

Supervisor: Franz Pfeiffer

High-sensitivity grating-based phase-contrast imaging at the Munich Compact Light Source - Computational Part

Using phase-contrast as alternative imaging contrast for X-rays can considerably improve the imaging results for biomedical specimens. This project will focus on the development of an algorithmic framework for a high-sensitivity and high-resolution grating-based phase-contrast micro-tomography setup at the Munich Compact Light Source for investigating soft-tissue biomedical samples, such biopsies. 

Character of thesis work: mainly computational (image processing/ reconstruction)  

For more information, please contact: Martin Dierolf (martin.dierolf@tum.de), Johannes Brantl (johannes.brantl@tum.de), or Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Biomedical Engineering and Medical Physics

Supervisor: Franz Pfeiffer

High-sensitivity grating-based phase-contrast imaging at the Munich Compact Light Source - Computational Part

Using phase-contrast as alternative imaging contrast for X-rays can considerably improve the imaging results for biomedical specimens. This project will focus on the development of an algorithmic framework for a high-sensitivity and high-resolution grating-based phase-contrast micro-tomography setup at the Munich Compact Light Source for investigating soft-tissue biomedical samples, such biopsies. 

Character of thesis work: mainly computational (image processing/ reconstruction)  

For more information, please contact: Martin Dierolf (martin.dierolf@tum.de), Johannes Brantl (johannes.brantl@tum.de), or Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Applied and Engineering Physics

Supervisor: Franz Pfeiffer

Radioluminescence microscopy for organoid specimens

Radioluminescence microscopy (RLM) is a novel approach for high-resolution imaging of the radionuclide uptake in living cells, particularly in organoid systems. This project will focus on the development of an experimental setup, which allows imaging the radionuclide distribution with a few micro-meter resolution, using a scintillator-lens CCD system. This project will be carried out in collaboration with the department of nuclear medicine at the TUM university hospital Klinikum rechts der Isar.

Character of thesis work: experimental (50%) / computational (50%)

For more information, please contact: Martin Dierolf (martin.dierolf@tum.de), Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Applied and Engineering Physics

Supervisor: Franz Pfeiffer

Radioluminescence microscopy for organoid specimens

Radioluminescence microscopy (RLM) is a novel approach for high-resolution imaging of the radionuclide uptake in living cells, particularly in organoid systems. This project will focus on the development of an experimental setup, which allows imaging the radionuclide distribution with a few micro-meter resolution, using a scintillator-lens CCD system. This project will be carried out in collaboration with the department of nuclear medicine at the TUM university hospital Klinikum rechts der Isar.

Character of thesis work: experimental (50%) / computational (50%)

For more information, please contact: Martin Dierolf (martin.dierolf@tum.de), Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Biomedical Engineering and Medical Physics

Supervisor: Franz Pfeiffer

Spectral material decomposition with dual-energy, photon-counting X-ray detectors for industrial applications

Despite being meanwhile well established and broadly available in medical imaging applications, spectral material decomposition using photon-counting hybrid pixel detectors is presently still underused in industrial imaging tasks. The main goal of this project is therefore to translate the existing theoretical and experimental knowledge from photon-counting biomedical imaging applications to industrial inspection applications. The work includes numerical programming tasks, such as implementing and refining decomposition algorithms,  and experimental tasks, such as taking several best practice measurement to classify different material separation applications for industrial end-users.

This master thesis will be carried out in collaboration with an external industrial collaborator located in the Munich area.

Character of thesis work: experimental physics (50%) & image processing (50%)

For more information, please contact: Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Applied and Engineering Physics

Supervisor: Franz Pfeiffer

Spectral material decomposition with dual-energy, photon-counting X-ray detectors for industrial applications

Despite being meanwhile well established and broadly available in medical imaging applications, spectral material decomposition using photon-counting hybrid pixel detectors is presently still underused in industrial imaging tasks. The main goal of this project is therefore to translate the existing theoretical and experimental knowledge from photon-counting biomedical imaging applications to industrial inspection applications. The work includes numerical programming tasks, such as implementing and refining decomposition algorithms,  and experimental tasks, such as taking several best practice measurement to classify different material separation applications for industrial end-users.

This master thesis will be carried out in collaboration with an external industrial collaborator located in the Munich area.

Character of thesis work: experimental physics (50%) & image processing (50%)

For more information, please contact: Franz Pfeiffer (franz.pfeiffer@tum.de)

suitable as

• Master’s Thesis Biomedical Engineering and Medical Physics

Supervisor: Franz Pfeiffer

Current and Finished Theses in the Group