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that's me.

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On this page I present a small part of my research work at my current affiliation (MRI segmentation) and my former affiliation (orbit segmentation). At the end, a list of my publications is made available.

MRI segmentation

MRI processing pipeline

I am currently working at MIRALab, University of Geneva, Switzerland as a Marie Curie Early Stage Researcher for the MultiScaleHuman project. My work is centered on the efficient extraction of muscolo-skeletal structure from MR images. Together with our hospital partner we have developed an acquisition protocol that allows us to generate seamless images that cover the complete. I have then implemented several pre-processing steps, including stitching, de-noising and bias field correction. Using the methods described in [BMT14a], I can label muscle tissue. Further work is on using deformable model segmentation for identification of individual muscles.

Orbit segmentation

Orbit segmentation

My previous research work at Welfenlab, Leibniz University of Hanover, was about the bony orbit. This structure is formed by the bones that hold the eye. Through high impact incidents, e.g. accidents or violence, the thin orbital floor can be easily fractured. Since it is not feasible to restore it, it has to be replaced by a titanium mesh. In my work I have developed a deformable model based segmentation technique to evaluate the outcome of the surgery. We compare the affected t orbit to the healthy one and evaluate several parameters. More information can be found in my master’s thesis and an upcoming paper. This work has been partly funded by the AO Foundation.


  1. Becker, M., & Magnenat-Thalmann, N. (2015). Muscle Tissue Labeling of Human Lower Limb in Multi-Channel mDixon MR Imaging: Concepts and Applications. Computational Biology And Bioinformatics, IEEE/ACM Transactions On, 1–10. doi:10.1109/TCBB.2015.2459679 Details
  2. Chincisan, A., Tecante, K., Becker, M., Magnenat-Thalmann, N., Hurschler, C., & Choi, H. F. (2015). A computational approach to calculate personalized pennation angle based on MRI: effect on motion analysis. International Journal Of Computer Assisted Radiology and Surgery, 1–11. doi:10.1007/s11548-015-1251-9 Details
  3. Becker, M., Nijdam, N., & Magnenat-Thalmann, N. (2015). Coupling strategies for multi-resolution deformable meshes: expanding the pyramid approach beyond its one-way nature. International Journal Of Computer Assisted Radiology and Surgery, 1–11. doi:10.1007/s11548-015-1241-y Details
  4. Wagner, M. E. H., Gellrich, N.-C., Friese, K.-I., Becker, M., Wolter, F.-E., Lichtenstein, J. T., … Essig, H. (2015). Model-based segmentation in orbital volume measurement with cone beam computed tomography and evaluation against current concepts. International Journal Of Computer Assisted Radiology and Surgery, 1–9. doi:10.1007/s11548-015-1228-8 Details
  5. Becker, M., Friese, K.-I., Wolter, F.-E., Gellrich, N.-C., & Essig, H. (2015). Development of a Reliable Method for Orbit Segmentation & Measuring. In 2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA 2015) (pp. 285–290). Torino, Italy. Details
  6. Becker, M., & Magnenat-Thalmann, N. (2014). Deformable Models in Medical Image Segmentation. In N. Magnenat-Thalmann, O. Ratib, & H. F. Choi (Eds.), 3D Multiscale Physiological Human (1st ed., pp. 81–106). London: Springer-Verlag London. doi:10.1007/978-1-4471-6275-9_4 Details
  7. Becker, M., & Magnenat-Thalmann, N. (2014). Muscle Tissue Labeling of Human Lower Extremities in Multi-Channel mDixon MR Imaging: Concepts and Applications. In Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on (pp. 279–284). doi:10.1109/BIBM.2014.6999168 Details
  8. Choi, H. F., Chincisan, A., Becker, M., & Magnenat-Thalmann, N. (2014). Multimodal composition of the digital patient: a strategy for the knee articulation. The Visual Computer, 30(6), 1–11. doi:10.1007/s00371-014-0983-9 Details
  9. Garcia Juan, D., Delattre, B. M. A., Trombella, S., Lynch, S., Becker, M., Choi, H. F., & Ratib, O. (2014). Open framework for management and processing of multi-modality and multidimensional imaging data for analysis and modelling muscular function. In Proc. SPIE (Vol. 9036). doi:10.1117/12.2042853 Details
  10. Assassi, L., Becker, M., & Magnenat-Thalmann, N. (2012). Dynamic skin deformation based on biomechanical modeling. In 25th Annual Conference on Computer Animation and Social Agents (CASA 2012). Details
  11. Becker, M. (2011). Modellbasierte Orbita-Segmentierung und die automatisierte Bestimmung anatomisch relevanter Parameter (Master’s thesis). Leibniz Universität Hannover, Germany. Details
  12. Stapel, K., Knauss, E., Schneider, K., & Becker, M. (2010). Towards Understanding Communication Structure in Pair Programming, 117–131. Details