Roxane Licandro


21.04.15 Radiologie 1136 ppkl

Dipl.-Ing. Dr. techn. Roxane Licandro, BSc
Email: roxane.licandro @
Phone: +43(0) 1 40400 73724

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

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

I am also affiliated with the Laboratory for Computational Neuroimaging at Massachusetts General Hospital and Harvard Medical School.

News and Upcoming

logo1 I am looking forward to giving a talk at the Meetup of the Austrian Society for Perinatal Medicine in Vienna from 17th - 18th of November 2023.
stage Join the Ultraschalltagung in Segau from 10th and 11th of November 2023. Wonderful occasion for me to be invited to talk about "AI for perinatal image analysis" in Leibnitz, Austria.
image Excited to be invited to give a talk at the lifespan MRI meeting at Trinity College Dublin on 19th of October 2023 in Dublin, Ireland. 
PIPPI Logo2023 Happy to host the workshop on Perinatal, Preterm and Paediatric Image Analysis  (PIPPI2023)  at MICCAI 2023 in Vancouver on 12th of October 2023.
Screenshot 2022 01 23 at 19.44.27 This year I will present our latest fetal work at the second FIT'NG conference taking place from 10 - 11th of September 2022 in Santa Rosa, California.
fluxlogo Excited that I received the FLUX Society travel grant to present our work about Ontogeny of the Ascending Arousal Network at FLUX Congress from 6th - 9th of September 2023.
Cluster Bildgebung EN3 Happy to support the scientific and organisational committee of the 5th Medical Imaging Cluster Festival at the Medical University of Vienna on June 15th 2023.


Our publication "Motion correction and volumetric reconstruction for fetal functional magnetic resonance imaging data" got accepted for publication in the Journal NeuroImage in July 2022. Link
Screenshot 2022 12 06 at 16.51.27 Excited to be honorable mentioned for outstanding review at the international conference on Medical Imaging with Deep Learning - MIDL 2022, Zurich (Switzerland), July 2022.

Research interests

  • Spatio-temporal modelling, statistical pattern analysis and computer vision
  • Fetal and pediatric brain development
  • Functional brain networks and plasticity
  • ExVivo MRI and Sudden Infant Death Syndrome (SIDS)
  • Treatment response assessment and predictive diagnosis

Short CV

Roxane Licandro graduated the master study of medical informatics at TU Wien with distinction in January 2016. She graduated her PhD studies in March 2021 at TU Wien in cooperation with CIR and worked as study assistant at Pattern Recognition and Image Processing (PRIP) Group,  and as teaching assistant at the  Institute of Computer Graphics and Algorithms and as university assistant at the Computer Vision Lab at TU Wien. Roxane Licandro was a postdoctoral research fellow at the Massachusetts General Hospital and Harvard Medical School until December 2022 and is currently a postdoc research associate at CIR in various projects with focus on spatio temporal modelling and machine learning.


Awards & Achievements

  • Flux Society Travel Grant 2023
  • Honorable mention for outstanding review - MIDL 2022, Zürich, Switzerland
  • ECR 2022 Best Research Presentation Abstract - European Congress of Radiology 2022
  • Nomination, Best Distance Learning Award 2021 - TU Wien
  • Team Nomination, Best Lecture Award 2019 - TU Wien
  • Marie Curie Alumni Association Micro Travel Grant, August 2018
  • Best Paper Award at the International Conference on Clinical and Medical Image Analysis ICCMIA'18, July 2018
  • 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)

Scientific Activities

Selected Recent Publications

Payette, K., Li, H., de Dumast, P., Licandro, R., Ji, H., Siddiquee, M.M.R., Xu, D., Myronenko, A., Liu, H., Pei, Y. and Wang, L., 2023. Fetal brain tissue annotation and segmentation challenge resultsMedical Image Analysis, p.102833.

Athena Taymourtash, Ernst Schwartz, Karl-Heinz Nenning, Daniel Sobotka, Roxane Licandro, Sarah Glatter, Mariana Cardoso Diogo, Polina Golland, Ellen Grant, Daniela Prayer, Gregor Kasprian, Georg Langs, Fetal development of functional thalamocortical and cortico–cortical connectivityCerebral Cortex, 2023; bhac446

Sobotka, D., Ebner, M., Schwartz, E., Nenning, K. H., Taymourtash, A., Vercauteren, T., Ourselin, S., Kasprian, G., Prayer, D., Langs, G., & Licandro, R. (2022). Motion Correction and Volumetric Reconstruction for Fetal Functional Magnetic Resonance Imaging Data. NeuroImage, 119213.

Lichtenegger R., Salas M., Sing A., Duelk M., Licandro R., Gesperger J., Baumann B., Drexler W., Leitgeb R., "Reconstruction of Optical Coherence Tomography Images Retrieved from Discontinuous Spectral Data using Conditional Generative Adversarial Network", Journal Biomedical Optics Express, 12, 6780-6795 (2021).

Licandro R., Hofmanninger J., Perkonigg M., Röhrich S., Weber M.-A., Wennmann M., Kintzele L., Piraud M., Menze B., Langs G., "Asymmetric Cascade Networks for Focal Bone Lesion Prediction in Multiple Myeloma", International Conference on Medical Imaging with Deep Learning (MIDL), London, July 2019.

Licandro R. and Schlegl T., Reiter M., Diem M., Dworzak M., Schumich A., Langs G., Kampel M., "WGAN Latent Space Embeddings for Blast Identification in Childhood Acute Myeloid Leukaemia, 24th International Conference on Pattern Recognition (ICPR) 2018, Beijing, August 2018.

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.


R. Licandro, "Longitudinal Diffeomorphic Fetal Brain Atlas Learning for Tissue Labeling using Geodesic Regression and Graph Cuts", TU Wien, January 2016. Link

R. Licandro, "Spatio Temporal Modelling of Dynamic Developmental Patterns", TU Wien, March 2021. Link