Biomedical Physics
Prof. Franz Pfeiffer
Research Field
Our interdisciplinary research portfolio is focused on the translation of modern x-ray physics concepts to biomedical sciences and clinical applications. We are particularly interested in advancing conceptually new approaches for biomedical x-ray imaging and therapy, and work on new kinds of x-ray sources, contrast modalities, and images processing algorithms. Our activities range from fundamental research using state-of-the-art, large-scale x-ray synchrotron and laser facilities to applied research and technology transfer projects aiming at the creation of improved biomedical device technology for clinical use. From a medical perspective, our work currently targets early cancer and osteoporosis diagnostics.
Address/Contact
James-Franck-Str. 1
85748 Garching b. München
+49 89 289 12552
Fax: +49 89 289 12548
Members of the Research Group
Professors
Photo | Degree | Firstname | Lastname | Room | Phone | |
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Prof. Dr. | Julia | Herzen | 2082 | +49 89 289-10806 | |
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Prof. Dr. | Franz | Pfeiffer | 2093 | +49 89 289-10827 |
Office
Photo | Degree | Firstname | Lastname | Room | Phone | |
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Nelly | de Leiris | 2091 | +49 89 289 12552 |
Scientists
Photo | Degree | Firstname | Lastname | Room | Phone | |
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Dr. | Klaus | Achterhold | 2087 | +49 89 289-12559 | |
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M.Sc. | Henriette | Bast | – | – | |
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M.Sc. | Daniel | Berthe | – | +49 89 289-12754 | |
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M.Sc. | Johannes | Brantl | – | +49 89 289-10846 | |
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Dr. | Madleen | Busse | – | +49 89 289-10802 | |
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Dr. | Martin | Dierolf | E.204 | +49 89 289-10824 | |
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M.Sc. | Tina | Dorosti Nadeali | – | – | |
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M.Sc. | Benedikt | Günther | – | – | |
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M.Sc. | Nikolai | Gustschin | – | +49 89 289-10843 | |
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M.Sc. | Jakob | Häusele | – | +49 89 289-12326 | |
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M.Sc. | Maximilian | Lochschmidt | – | +49 89 289-12591 | |
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M.Sc. | Johannes | Melcher | 1.110 | +49 89 289-10846 | |
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Dr. | Florian | Schaff | – | +49 89 289-10802 | |
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Rafael Christian | Schick | – | – | ||
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M.Sc. | Thorsten | Sellerer | 2702 | +49 89 289-12672 | |
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M.Sc. | Kirsten | Taphorn | – | +49 89 289-12562 | |
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M.Sc. | Theresa | Urban | – | – | |
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Dipl.-Phys. | Marian | Willner | 2710 | – |
Students
Photo | Degree | Firstname | Lastname | Room | Phone | |
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Arathy | Bastin | – | – | ||
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B.Sc. | Lennart | Forster | – | – | |
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Patrick | Ilg | – | +49 89 289-10820 | ||
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B.Sc. | Lennard | Kaster | – | – | |
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B.Sc. | Michael | Mörtl | – | +49 89 289-10883 | |
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B.Sc. | Gloria | Müller | – | – | |
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B.Eng. | Kacper | Ogórek | – | – | |
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B.Sc. | Annika | Ries | – | – | |
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B.Sc. | Mikhail | Samsonov | – | +49 89 289-10883 | |
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B.Sc. | Oliver | Schurius | – | – | |
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B.Eng. | Merrin | Tharakan | – | +49 89 289-10820 |
Other Staff
Teaching
Course with Participations of Group Members
Offers for Theses in the Group
- AI in Physics: Convolutional neural networks for dark-field X-ray CT reconstruction
Grating-based X-ray dark-field imaging uses scattering of X-rays to create an image of an object, rather than conventional X-ray attenuation. The combination of X-ray scattering with imaging allows us to map information about structures that are much smaller than the resolution of the imaging system over a large field of view. X-ray dark-field imaging can be combined with computed tomography (CT) to create three-dimensional images of the scattering distribution inside an object. DF-CT was recently implemented for the first time into a clinical CT here at TUM (https://www.bioengineering.tum.de/en/news/details/new-technology-for-clinical-ct-scans). The goal of this project is to use convolutional neural networks (CNNs) to remove sampling artefacts in DF-CT images. Due to the unavailability of training data from the DF-CT machine, a technologically similar experimental setup and apply transfer learning will be used. The student will acquire, process and prepare training data, as well as train and apply CNNs. Character of thesis work: mainly computational physics & image processing 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
- AI in Physics: Convolutional neural networks for dark-field X-ray CT reconstruction
Grating-based X-ray dark-field imaging uses scattering of X-rays to create an image of an object, rather than conventional X-ray attenuation. The combination of X-ray scattering with imaging allows us to map information about structures that are much smaller than the resolution of the imaging system over a large field of view. X-ray dark-field imaging can be combined with computed tomography (CT) to create three-dimensional images of the scattering distribution inside an object. DF-CT was recently implemented for the first time into a clinical CT here at TUM
(https://www.bioengineering.tum.de/en/news/details/new-technology-for-clinical-ct-scans).
The goal of this project is to use convolutional neural networks (CNNs) to remove sampling artefacts in DF-CT images. Due to the unavailability of training data from the DF-CT machine, a technologically similar experimental setup and apply transfer learning will be used. The student will acquire, process and prepare training data, as well as train and apply CNNs.
Character of thesis work: mainly computational physics & image processing
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
- Dark-field Chest X-ray Imaging: Advanced image processing for clinical applications
Dark-field radiography exploits the scattering of X-rays to visualize structures below the resolution limit. Currently, several initial clinical patient studies are underway on a worldwide first prototype we recently realized at Klinikum rechts der Isar. Within the framework of this project, the special algorithms for image post-processing of these first clinical data will be further optimized and used together with the participating radiologists for the evaluation of better direction of lung diseases.
Character of thesis work: mainly computational physics & image processing
For more information, please contact: Rafael Schick (rafael.schick@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de).
- suitable as
- Master’s Thesis Biomedical Engineering and Medical Physics
- Supervisor: Franz Pfeiffer
- Dark-field Chest X-ray Imaging: Advanced image processing for clinical applications
Dark-field radiography exploits the scattering of X-rays to visualize structures below the resolution limit. Currently, several initial clinical patient studies are underway on a worldwide first prototype we recently realized at Klinikum rechts der Isar. Within the framework of this project, the special algorithms for image post-processing of these first clinical data will be further optimized and used together with the participating radiologists for the evaluation of better direction of lung diseases.
Character of thesis work: mainly computational physics & image processing
For more information, please contact: Rafael Schick (rafael.schick@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de).
- suitable as
- Master’s Thesis Applied and Engineering Physics
- Supervisor: Franz Pfeiffer
- Dark-field Chest X-ray Imaging: Development of registration algorithms for the analysis of functional lung images
Dark-field radiography exploits the scattering of X-rays to reveal structures in lung tissue that cannot be visualized with conventional imaging. Currently, several initial clinical patient studies are underway on a worldwide first prototype we recently realized at Klinikum rechts der Isar. Within the scope of this project, special registration algorithms are to be developed that can register thorax images in inhalation and exhalation and allow local differences between ventilation states (for example in certain lung diseases).
Character of thesis work: mainly computational physics & image processing
For more information, please contact: Rafael Schick (rafael.schick@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de).
- suitable as
- Master’s Thesis Applied and Engineering Physics
- Supervisor: Franz Pfeiffer
- Dark-field Chest X-ray Imaging: Development of registration algorithms for the analysis of functional lung images
Dark-field radiography exploits the scattering of X-rays to reveal structures in lung tissue that cannot be visualized with conventional imaging. Currently, several initial clinical patient studies are underway on a worldwide first prototype we recently realized at Klinikum rechts der Isar. Within the scope of this project, special registration algorithms are to be developed that can register thorax images in inhalation and exhalation and allow local differences between ventilation states (for example in certain lung diseases).Character of thesis work: mainly computational physics & image processing
For more information, please contact: Rafael Schick (rafael.schick@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de).
- suitable as
- Master’s Thesis Biomedical Engineering and Medical Physics
- Supervisor: Franz Pfeiffer
- Dark-field Chest X-ray Imaging: Monte Carlo based simulation of Compton scattering
Dark-field radiography is a novel X-ray imaging technique that is being tested for the first time in clinical patient studies on a worldwide first prototype recently completed by us at the TUM Klinikum rechts der Isar. Within the scope of this project, Monte Carlo based Compton simulations will be developed, which will allow an exact modelling of the Compton scattering and thus a better correction of the image artifacts.
Character of thesis work: experimental physics (50%) & computational physics (50%).
For more information, please contact: Henriette Bast (henriette.bast@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de).
- suitable as
- Master’s Thesis Biomedical Engineering and Medical Physics
- Supervisor: Franz Pfeiffer
- Dark-field Chest X-ray Imaging: Monte Carlo based simulation of Compton scattering
Dark-field radiography is a novel X-ray imaging technique that is being tested for the first time in clinical patient studies on a worldwide first prototype recently completed by us at the TUM Klinikum rechts der Isar. Within the scope of this project, Monte Carlo based Compton simulations will be developed, which will allow an exact modelling of the Compton scattering and thus a better correction of the image artifacts.
Character of thesis work: experimental physics (50%) & computational physics (50%).
For more information, please contact: Henriette Bast (henriette.bast@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de).
- suitable as
- Master’s Thesis Applied and Engineering Physics
- Supervisor: Franz Pfeiffer
- Dark-field X-ray microCT: Pre-clinical research on improved lung disease detection
Dark-field computed tomography uses the wave property of X-rays to provide complementary contrasts in X-ray imaging. In this project, an existing prototype for dark-field CT in mice will be used to explore the use of dark-field contrast in pre-clinical research for improved detection of lung diseases in collaboration with the Helmholtz Center for Health. In addition to experimental work to support the conduct of the preclinical studies, algorithmic research to reduce image noise and dose is planned.
Character of thesis work: experimental medical physics (60%) & image processing (40%).
For more information, please contact: Benedikt Guenther (benedikt.guenther@mytum.de), Simon Zandarco (simon.zandarco@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de).
- suitable as
- Master’s Thesis Biomedical Engineering and Medical Physics
- Supervisor: Franz Pfeiffer
- Dark-field X-ray microCT: Pre-clinical research on improved lung disease detection
Dark-field computed tomography uses the wave property of X-rays to provide complementary contrasts in X-ray imaging. In this project, an existing prototype for dark-field CT in mice will be used to explore the use of dark-field contrast in pre-clinical research for improved detection of lung diseases in collaboration with the Helmholtz Center for Health. In addition to experimental work to support the conduct of the preclinical studies, algorithmic research to reduce image noise and dose is planned.
Character of thesis work: experimental medical physics (60%) & image processing (40%).
For more information, please contact: Benedikt Guenther (benedikt.guenther@mytum.de), Simon Zandarco (simon.zandarco@tum.de) or Franz Pfeiffer (franz.pfeiffer@tum.de).
- suitable as
- Master’s Thesis Applied and Engineering Physics
- Supervisor: Franz Pfeiffer
Current and Finished Theses in the Group
- Characterization of Clinical Spectral CT Systems for Diagnosis of Myocardial Ischemia
- Abschlussarbeit im Masterstudiengang Biomedical Engineering and Medical Physics
- Themensteller(in): Franz Pfeiffer
- Dynamic X-ray Dark-field Tomography for Generating Deep Learning Training Datasets
- Abschlussarbeit im Masterstudiengang Biomedical Engineering and Medical Physics
- Themensteller(in): Franz Pfeiffer
- Influence of Foreign Bodies in X-Ray Dark-Field Radiography of the Human Chest
- Abschlussarbeit im Masterstudiengang Biomedical Engineering and Medical Physics
- Themensteller(in): Franz Pfeiffer
- Exploring the Degeneration of Intervertebral Discs using Staining-Based X-ray MicroCT Imaging
- Abschlussarbeit im Masterstudiengang Physics (Applied and Engineering Physics)
- Themensteller(in): Franz Pfeiffer
- Hyperspectral Imaging for Residual Moisture Detection in Lithium-ion Battery Electrodes
- Abschlussarbeit im Masterstudiengang Physik (Physik der kondensierten Materie)
- Themensteller(in): Franz Pfeiffer
- Implementation and characterization of a two-grating interferometer for AXDT measurements with a robotic arm
- Abschlussarbeit im Masterstudiengang Biomedical Engineering and Medical Physics
- Themensteller(in): Franz Pfeiffer
- X-ray Diffraction Imaging using Coded Aperture Mask
- Abschlussarbeit im Masterstudiengang Biomedical Engineering and Medical Physics
- Themensteller(in): Franz Pfeiffer
- Monitoring the behavior of silver-containing medical products using K-edge Subtraction imaging at the Munich Compact Light Source and Dual Energy Computed Tomography at SKYSCAN
- Abschlussarbeit im Masterstudiengang Biomedical Engineering and Medical Physics
- Themensteller(in): Franz Pfeiffer