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Medical Physics and Metrological Information Technology

Division 8

Developing measuring methods and measuring procedures in medicine is one major task of Division 8. Furthermore, the other is information technology - from mathematical modelling and software testing to the approval of gaming machines.

Head of Division

Tobias Schäffter studied electrical engineering and computer science at TU-Berlin until 1993 and obtained his PhD degree in magnetic resonance (MR) spectroscopic imaging at University Bremen (Prof. Leibfritz) in 1996. From 1996-2006, he worked as a Principal Scientist at the Philips Research Laboratories in Hamburg (Germany). He was responsible for the development of new MR-acquisition and reconstruction techniques as well as investigation of MR-compatible devices. He managed the clinical evaluation and product integration of industrial research.

In April 2006, Professor Schäffter took up the post as the Philip Harris Professor of Imaging Sciences at King’s College London. A major aim of his research is the investigation of fast and quantitative imaging techniques for cardiovascular applications with a strong focus on translation of biomedical engineering into clinical practice. From 2012 to 2015, he was department head of biomedical engineering and the deputy head of the division in imaging sciences. He taught in the BSc and MSc programmes of Biomedical Engineering. As director of the EPSRC doctorial training centre in medical imaging he was responsible for the PhD training programme between King’s and Imperial College London.

Since 2015 he heads the Division 8 of Medical Physics and Metrological Information Technology at Physikalisch-Technische Bundesanstalt (PTB) in Berlin, where he is responsible for the development of new quantitative measurement and reference techniques in medicine. He is the co-Spokesman of the doctoral training centre in quantitative Imaging of biophysical parameter BioQic at Charité Berlin. Since 2019 he is also a Professor in Biomedical Imaging at Technical University Berlin and the Einstein Centre Digital Future. Tobias Schäffter is member of the Berlin-Brandenburg Academy of Sciences.

Research Areas 

  • Medical Physics, Biomedical Engineering, Imaging Sciences, Data Science
  • Magnetic Resonance Imaging (MRI)
  • Reference Methods and physical Standards (phantoms)
  • Interventional and Cardiovascular MRI
  • Quantitative MRI
  • Simultaneous PET-MRI
  • Clinical Translation

Publications 

ORCID iD iconorcid.org/0000-0003-1310-2631

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Curriculum Vitae

CV

Abt. 8, Abteilungsbericht aus dem Jahresbericht

Der Opens external link in new windowAbteilungsbericht gibt einen Überblick über die wichtigsten Nachrichten und Ereignisse der Abteilung „Medizinphysik und metrologische Informationstechnik“ des letzten Jahres und ergänzt somit den Opens external link in new windowJahresbericht 2021 der PTB.

DepartmentsDepartments

Tasks

Improvement in accuracy and reliability of

  • measuring methods and testing procedures in medicine for quality assurance in diagnostics and therapy
  • information processing components of scientific, industrial, and consumer protection oriented metrology.

Medical physics: Development of new measuring techniques and testing procedures for medical diagnostics, in particular laser-assisted measuring techniques, NMR-tomography and -spectroscopy, magneto cardiography and -encephalography (PTB Biomagnetic Center in Berlin), development and calibration of testing devices and reference materials.

Metrological information technology: Quality assurance for the use of information-technological means in metrology, especially in data acquisition , storage and processing. The area of work covers hard- and software problems as well as mathematical problems, the focuses being methods of digitizing, interfaces, communication components, software quality assurance, databases, numerical modelling and mathematical algorithms of measurement data processing, including relevant testing methods and tools. Pattern evaluation of cash gaming machines and voting machines in accordance with legal regulations.

 

 

Colloquium

 

 

 

 

 

Colloquium of Division 8

„Medical Physics and Metrological IT“

 

 

Location:

Physikalisch-Technische Bundesanstalt, Institut Berlin,

Abbestraße 2-12

10587 Berlin (Charlottenburg)

 

Contact:  

anett.pfeiffer(at)ptb.de , Tel.: (0049 30) 3481 7307  

 

The aim of the colloquium is the inderdisciplinary exchange between fundamental and application-oriented research in the fields of medical physics and metrological IT. The colloquium hopes to support a dialogue between researchers, clinicians and representatives of industry. To this end, experts from various disciplines are invited to relay new theoretical and experimental approaches, and to discuss mutual fields of research from differing viewpoints. The colloquium is open to all PTB employees and guests.

 

Programme 2022:

 

30.03.2022
03:45 p.m.
WebEx

Prof. Dr. Julia Schnabel
Technische Universität München (TUM), Fakultät für Informatik:
"AI-enabled cardiac MRI"

29.04.2022
11:00 a.m.
Hörsaal HvH
& Webex

Prof. Dr. Sebastian Kozerke,
ETH Zürich, Dep. Informationstechnologie und Elektrotechnik:
"Image Reconstruction and Inference - About Inverse Problems and Crimes" 


22.06.2022
01:00 p.m.
Hörsaal HvH
& Webex

PD Dr. habil. Michael Graß,
Principal Scientist, Philips Research:
"Artificial Intelligence in X-ray based Medical Imaging" 



29.06.2022
1:00 p.m.
Hörsaal HvH
& Webex

Prof. Dr. Abdulla Ghani,
Technische Universität Berlin, Mechanical Engineering and Transport Systems:
"Machine Learning meets High-fidelity numerical combustion simulations" 

 

27.07.2022
11:00 a.m.
Hörsaal HvH
& Webex

Prof. Dr. Nils Strodthoff,
Carl von Ossietzky Universität Oldenburg:
"Machine Learning for Medical Time Series- Challenges and Solutions" 

 

06.10.2022
11:00 a.m.
Hörsaal HvH
& Webex

Prof. Dr. Thomas Deserno,
Peter L. Reichertz Institut für Medizinische Informatik, TU Braunschweig:
"tba" 


 

Videos of past presentations:

 

Prof. Dr. Sebastian Kozerke,
ETH Zürich, Dep. Informationstechnologie und Elektrotechnik:
"Image Reconstruction and Inference - About Inverse Problems and Crimes" 

The video is only available PTB-internally. Please get in touch with Anett Pfeiffer. 

 

Prof. Dr. Julia SchnabelTechnische Universität München (TUM), Fakultät für Informatik:
"AI-enabled cardiac MRI" 

30.3.2022

Opens external link in new windowVideo

 

Prof. Dr. Jochen Guck, Max-Planck-Institut für die Physik des Lichtes, Erlangen: 
"Physical phenotyping at rates of 1,000 cells/sec"

09.12.2021

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Prof. Dr. Skyler Degenkolb, Physikalisches Institut, Universität Heidelberg: 
"Quantum sensing for precision measurements: warm atoms and ultracold neutrons"

11.11.2021

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Prof. Dr. & Dipl.-Ing. Sylvia Thun, Core Facility "Digital Medicine and Interoperability", Berlin Institute of Health (BIH) @ Charité:
"Enabling interoperability of information and processes across health domains"

18.10.2021

Opens external link in new windowVideo

 

Prof. Oliver WiebenUniversity of Wisconsin-Madison, Depts. of Medical Physics & Radiology: "MRI Flow Imaging: Validation, Assessment of Complex Hemodynamics, and the Power of Functional Challenges"

23.08.2021

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Dr. Jordi AlstrueyKing's College London, Department of Biomedical Engineering: „Databases of in silico pulse waves for haemodynamic studies"

25.02.2021

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News

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Die Europäische Kooperation im gesetzlichen Messwesen erarbeite europäische harmonisierte technische Interpretationen für die in den europäischen Richtlinien (31/2014/EU und 32/2014/EU) geregelten Messgerätearten. 

Die WELMEC-Arbeitsgruppe 7 „Software“ hat u.a. einen neuen Anhang „O“ (O für General-Purpose Operating Systems) für den WELMEC Guide 7.2 „Software“ erarbeitet und entsprechende...

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Andreas Kofler (PTB) published together with Christian Wald (Charité–Universitätsmedizin Berlin), Markus Haltmeier (University of Innsbruck), Tobias Schäffter (PTB) and Christoph Kolbitsch (PTB) an article about a method for image reconstruction based on convolutional dictionary learning.

The method can be seen as a physics-informed and supervised method fo learnind a convolutional dictionary....

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