Roxane Licandro

Contact

     Roxane Licandro

      Dipl.-Ing. Roxane Licandro, BSc
      Email: roxane.licandro @ tuwien.ac.at

      Computational Imaging Research Lab
      Department of Biomedical Imaging and Image-guided Therapy
      Medical University of Vienna
      Waehringer Guertel 18-20
      A-1090 Vienna / Austria

Office
Anna Spiegel Center of Translational Research
(building 25, floor 7, room 27)

I am also affiliated with the Computer Vision Lab at the Vienna University of Technology, where I am currently working as project assistant in the FlowCLUSTER Project.

Research interests

  • Spatio-temporal modelling
  • Diffeomorphic registration
  • Fetal and pediatric brain development
  • Functional brain networks and plasticity
  • Automatic MRD Assessment in Leukaemia

Short CV

Roxane Licandro graduated the master study of medical informatics at the Vienna University of Technology (TU Wien) with distinction in January 2016.  She worked as study assistant and teaching assistant at the Pattern Recognition and Image Processing (PRIP) Group,  and as teaching assistant at the  Institute of Computer Graphics and Algorithms and the Computer Vision Lab at TU Wien. She joined the CIR-Lab in summer 2012 and wrote her master’s thesis in cooperation with CVL and the CIR-Lab. She is currently engaged in her PhD studies at TU Wien in cooperation with CIR.

Projects

  • FETALMORPHO
  • Reorgansiation of semantic language brain networks after paediatric stroke

Awards & Achievements

  • February 2017 – July 2017 Marie Skłodowska Curie Fellowship within the European Project AutoFLOW
  • Best Poster Award – 3rd Austrian Biomarker Symposium on Early Diagnostics 2016 (3rd Place)

Selected Recent Publications

Licandro R., Reiter M., Diem M., Dworzak M., Schumich A., Kampel M., ” Application of Machine Learning for Automatic MRD Assessment in Paediatric Acute Myeloid Leukaemia”, 7th International Conference on Pattern Recognition Applications and Methods, Funchal - Madeira (Portugal), January 2018. PDF

Licandro R. Nenning K.H., Schwartz E., Kollndorfer K., Bartha-Doering L., Liu H., Langs G. Assessing Reorganisation of Functional Connectivity in the Infant Brain. In: Cardoso M. et al. (eds) Fetal, Infant and Ophthalmic Medical Image Analysis. FIFI 2017, OMIA 2017. Lecture Notes in Computer Science, vol 10554. Springer, Cham. Quebéc (Canada), September 2017.PDF

Licandro R., Langs G., Kasprian G., Sablatnig R. Prayer D., Schwartz E., " Longitudinal Atlas Learning for Fetal Brain Tissue Labeling using Geodesic Regression", WiCV Workshop at the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas (U.S.), July 2016.

Thesis

R. Licandro, "Longitudinal Diffeomorphic Fetal Brain Atlas Learning for Tissue Labeling using Geodesic Regression and Graph Cuts", Vienna University of Technology, January 2016. Link