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Detail

Roxane Licandro
Dr.techn Dipl.-Ing. Roxane Licandro, BSc

Department of Biomedical Imaging and Image-guided Therapy
Position: Research Associate (Postdoc)

ORCID: 0000-0001-9066-4473
T +43 1 40400 73724
roxane.licandro@meduniwien.ac.at

Further Information

Keywords

Artificial Intelligence; Pattern Recognition, Automated; Spatio-Temporal Analysis

Research group(s)

Research interests

My main research focus lies on finding new ways to computationally model and predict dynamic processes in space and over time, especially in the field of fetal and paediatric brain development, functional brain networks and plasticity, bone lesion prediction in multiple myeloma and in the field of automatic MRD assessment in childhood leukaemia.

Techniques, methods & infrastructure

  • Diffeomorphic registration
  • Machine learning and statistical pattern analysis
  • Spatio temporal modelling and anomaly prediction
  • Computer vision
  • High resolution reconstruction and motion correction

Selected publications

  1. Korom M., Camacho C., Filippi C.A., Licandro R., Moore L., Dufford A., Zöllei L., Graham A., Spann M., Howell B., FIT'NG, Shultz S., Scheinost D., 2022. Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies. Developmental Cognitive Neuroscience, 53, p.101055. Available at: http://dx.doi.org/10.1016/j.dcn.2021.101055.
  2. Lichtenegger R., Salas M., Sing A., Duelk M., Licandro R., Gesperger J., Baumann B., Drexler W., Leitgeb R., 2021. Reconstruction of visible light optical coherence tomography images retrieved from discontinuous spectral data using a conditional generative adversarial network. Biomedical Optics Express, 12(11), p.6780. Available at: http://dx.doi.org/10.1364/BOE.435124.
  3. Sobotka D., Licandro R., Ebner M., Schwartz E., Vercauteren T., Ourselin S., Kasprian G., Prayer D., Langs G. et al., 2019. Reproducibility of Functional Connectivity Estimates in Motion Corrected Fetal fMRI. Lecture Notes in Computer Science, pp.123–132. Available at: http://dx.doi.org/10.1007/978-3-030-32875-7_14.
  4. R. Licandro and T. Schlegl, M. Reiter, M. Diem, M. Dworzak, A. Schumich, G. Langs, M. Kampel, 2018. WGAN Latent Space Embeddings for Blast Identification in Childhood Acute Myeloid Leukaemia. 2018 24th International Conference on Pattern Recognition (ICPR). Available at: http://dx.doi.org/10.1109/ICPR.2018.8546177.
  5. R. Licandro, K.-H. Nenning, E. Schwartz, K. Kollndorfer, L. Bartha-Doering, H. Liu, G. Langs, 2017. Assessing Reorganisation of Functional Connectivity in the Infant Brain. Lecture Notes in Computer Science, pp.14–24. Available at: http://dx.doi.org/10.1007/978-3-319-67561-9_2.