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Licandro Roxane

  1. Universitätsklinik für Radiologie und Nuklearmedizin
  2. Unsere Abteilungen
  3. CIR
  4. Team
  5. Licandro Roxane
Licandro Roxane|© Christian Houdek

Univ. Ass. DI Dr.techn. Roxane Licandro BSc

Head of Early Life Image Analysis (ELIA) Group

Contact

E-Mail: roxane.licandro@meduniwien.ac.at
Phone: +43 (0)1 40400 73723

Computational Imaging Research Lab
Head of Early Life Image Analysis (ELIA) Group
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 Laboratory for Computational Neuroimaging at Massachusetts General Hospital and Harvard Medical School.

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. She is currently working as PostDoc research associate at CIR in various projects with focus on early life image analysis, spatio temporal modelling in combination with machine learning.

News

Congratulations Simon Gutwein on receiving the Best Poster Presentation Award at the UNSURE Workshop at MICCAI 2024 in Marrakech, Marokko! Link Video, Link Paper!

Happy to announce that I will be a lecturer at the Winter School in the course of the European Project STRIKE held in Vienna from 17th - 19th of February 2025, organised by the Medical Imaging Plattform (MIP) at the Medical University of Vienna. More information following soon.

 

Join us at MICCAI 2024. We are co-organizers of the PIPPI Workshop and FeTA Challenge taking place on the 6th of October 2024 in Marrakech, Marokko. Also check out our recent work regarding synthetic contrastive learning for genetic aberration detection that will be presented at the UNSURE Workshop on the 10th of October 2024.

 

I am looking forward to talk at the 62. Jahrestagung der Österreichischen Gesellschaft für Kinder- und Jugendheilkunde held in Bregenz (Austria) from 3rd - 5th of October 2024. Link

 

 

 

Research interests

  • Spatio-temporal modelling
  • Fetal and pediatric brain development
  • Functional brain networks and plasticity
  • Automatic MRD assessment in leukaemia
  • Statistical pattern analysis and computer vision

Awards & Achievements

  • Best Paper Nomination ICPRAM 2024 Rome, Italy
  • Flux Society Travel Award 2023, FLUX Congress at Santa Rosa, California, US
  • Honorable Mention for outstanding review - International Conference on Medical Imaging and Deep Learning 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)

Projects

Scientific Activities

  • Member of the Organizing Committee of CVPR2017-WiCV,  MICCAI-DATRA 2018, MICCAI-PIPPI (since 2018), BrainHackVienna2019, FeTA Challenge (since 2021), FIT'NG FLUX2021, MIC Festival (since 2020), FIT'NG Conference 2022
  • Communications Committee Member Fetal, Infant, Toddler Neuroimaging Group (FIT'NG) since 2021.
  • MICCAI Student Board President (Nov. 2017 - Nov. 2019)
  • Program Committee Member/Reviewer MICCAI-RAMBO 2017, MICCAI-FIFI, CIARP, CVPR-WDiCV, ICCV-WiCV2018, ACV (since 2018), MICCAI, ICMLA, IPMI (since 2021), DGM4MICCAI (since 2021), MIDL 2022, Med-Neurips 2022, CVWW 2023
  • Journal Review Medical Image Analysis, Magnetic Resonance Imaging, Journal on Computing and Cultural Heritage, Machine Vision and Application, European Radiology, NeuroImage, NeuroImage Clinical, Scientific Report, Cerebral Cortex
     

Selected recent publications

  • S. Gutwein, M. Kampel, S. Taschner-Mandl, R. Licandro, FISHing in Uncertainty: Synthetic Contrastive Learning for Genetic Aberration Detection, In MICCAI 2024 Workshop Proceedings of Uncertainty for Safe Utilization of Machine Learning in Medical Imaging. UNSURE 2024. Lecture Notes in Computer Science. Springer, Cham. October 2024
  • 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 results. Medical Image Analysis, p.102833. 2023
  • A. Taymourtash, E. Schwartz, K.-H. Nenning, D. Sobotka, R. Licandro, S. Glatter, Mariana C. Diogo, P. Golland, E. Grant, D. Prayer, G. Kasprian, G. Langs, Fetal development of functional thalamocortical and cortico–cortical connectivity, Cerebral 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., "Motion Correction and Volumetric Reconstruction for Fetal Functional Magnetic Resonance Imaging Data", NeuroImage, April 2022, https://doi.org/10.1016/j.neuroimage.2022.119213
  • A. Lichtenegger, J. Tamaoki, R. Licandro, T. Mori, P. Mukherjee, L. Bian, S. Makita, S. Matsusaka, M. Kobayashi, B. Baumann, Y. Yasuno, "Longitudinal investigation of a xenograft tumor zebrafish model using polarization-sensitive optical coherence tomography". Scientific Report 12, 15381 (2022). https://doi.org/10.1038/s41598-022-19483-z
  • 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. https://arxiv.org/abs/1907.13539.
  • 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. 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. MICCAI 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", TU Wien, January 2016. https://doi.org/10.34726/hss.2015.21890
R. Licandro, "Spatio Temporal Modelling of Dynamic Developmental Patterns", TU Wien, March 2021. https://doi.org/10.34726/hss.2021.39603