Dr. Wolfgang Wein

Current Occupation

I am CEO of the R&D lab ImFusion and a senior research scientist in the field of medical image computing, working in the interdisciplinary cross-section of computer science, physics and medicine. Recent research focuses on improved 3D cone-beam X-Ray reconstruction techniques, including novel motion compensation approaches. Another area of interest (based on prior work at Siemens Corporate Research, Princeton), is ultrasound-based interventional navigation in various clinical specialties and all its associated computational challenges.

We are currently looking for students for internships and student projects. Please check the job page at ImFusion for more details.

Curriculum Vitae

  • 10/1999 - 01/2004: Computer science (minor physics) at Technische Universität München.
  • 02/2001 - 04/2001: Internship at the IT department of the Infineon maskhouse (MH DPT), Munich (evaluation of log files of litographic mask writers for statistical process control).
  • 02/2002 - 04/2002: Interdisciplinary project at the new experimental nuclear reactor FRM-II in Garching (development of a framework for network based instrument control of neutron scattering experiments).
  • 07/2002 - 09/2002: Participation in the IBM Extreme Blue Summer Internship in Boeblingen. I was working in the Life Science project and developed an integrated 2D/3D chemical structure editor.
  • 04/2003 - 10/2003: Internship at Siemens Corporate Research , Princeton, USA. Within the scope of my diploma thesis I was working on 2D/3D registration for patient positioning in radiation therapy.
  • 11/2003 - 02/2006: Ph.D. student at the new chair I16 of Prof. Nassir Navab, in collaboration with Siemens Corporate Research.
  • 03/2006 - 04/2010: Research Scientist at Siemens Corporate Research, Princeton NJ USA.
  • 05/2010 - 07/2012: CTO at White Lion Technologies AG, Munich, Germany.
  • 08/2012 - today: CEO at ImFusion GmbH, Munich, Germany.

Dissertation

Title: Multimodal Integration of Medical Ultrasound for Treatment Planning and Interventions


Abstract: Ultrasound is a popular, cost-effective and non-invasive medical imaging modality. If an ultrasound probe is equipped with a 3D position sensor, the acquired images can be obtained in their spatial context, a technique commonly denoted "3D freehand ultrasound".
Combining ultrasound and a pre-operative Computed Tomography (CT) scan of the same patient can be beneficial for a number of clinical applications. The core of this thesis is the development of novel methods for fully automatic alignment (i.e. registration) of 3D freehand ultrasound and CT data, based on the image content and the physical properties of both modalities.
In particular, a new method is proposed which simultaneously optimizes the linear combination of different ultrasonic effects simulated from CT, and the parameters for spatial alignment. This original concept allows local as well as global optimization of the simulation parameters, resulting in optimal registration of any modalities, where usual registration solutions do not succeed and explicit simulation of complex effects are necessary.
Furthermore, we introduce new techniques for 3D freehand ultrasound calibration and reconstruction, as well as visualization of fused CT and ultrasound data.
Two clinical applications are investigated in detail. We use a designated version of an automatic registration algorithm to integrate diagnostic ultrasound into radiation treatment planning for head and neck cancer. Our simultaneous optimization of simulation and registration is applied, in the context of treating liver and kidney metastases, for fusing CT with both diagnostic and interventional ultrasound of the abdomen. While diagnostic fusion helps doctors to assess indeterminate lesions in those organs, interventional fusion using our techniques allows for advanced image-guided navigation, in particular, for needle biopsies and radio-frequency ablations.

 

Dissertation Download as PDF

Diploma Thesis

My Diploma Thesis with the title Intensity Based Rigid 2D-3D Registration Algorithms for Radiation Therapy.