I am a CNRS researcher at the Brain and Spine Institute (ICM), in the ARAMIS Lab (Paris). I first joined the ARAMIS Lab as a postodoctoral researcher in 2017, after having been awarded a PRESTIGE incoming mobility co-financing grant, with the aim to develop computational imaging tools to improve the understanding and diagnosis of dementia. I did my PhD at University College London (UCL) in the Translational Imaging Group, part of the Centre for Medical Image Computing (CMIC), under the supervision of Prof. Sébastien Ourselin. The main focus of my PhD has been to develop image synthesis algorithms for MR-based attenuation correction in hybrid PET/MR scanners, and for detecting pathological abnormalities in the reconstructed PET data. At the end of my PhD in 2016, I received funding from the CMIC-EPSRC Platform Grant to explore a new field of research. During this one-year postdoc at UCL I decided to tackle the problem of automatic MR-based radiotherapy treatment planning in the pelvic region by developing a new framework combining segmentation and image synthesis.
You can check my CV here.
- Samper-González, J., Burgos, N., Bottani, S., Fontanella, S., Lu, P., Marcoux, A., Routier, A., Guillon, J., Bacci, M., Wen, J., Bertrand, A., Bertin, H., Habert, M.-O., Durrleman, S., Evgeniou, T., and Colliot, O.: Reproducible Evaluation of Classification Methods in Alzheimer’s Disease: Framework and Application to MRI and PET Data. NeuroImage, 183: 504–521, 2018. doi:10.1016/j.neuroimage.2018.08.042 Available on HAL.
- Burgos, N., Samper-González, J., Bertrand, A., Habert, M.-O., Ourselin, S., Durrleman, S., Cardoso, M.J., and Colliot, O.: Individual Analysis of Molecular Brain Imaging Data through Automatic Identification of Abnormality Patterns. In Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment, LNCS, 10555: 13–22, Springer, 2017. doi:10.1007/978-3-319-67564-0_2
- Burgos, N., Guerreiro, F., McClelland, J., Presles, B., Modat, M., Nill, S., Dearnaley, D., deSouza, N., Oelfke, U., Knopf, A.-C., Ourselin, S., and Cardoso, M.J.: Iterative Framework for the Joint Segmentation and CT Synthesis of MR Images: Application to MRI-Only Radiotherapy Treatment Planning. Physics in Medicine and Biology, 62(11): 4237, 2017. doi:10.1088/1361-6560/aa66bf An invited paper in the Special Issues of Physics in Medicine and Biology on Recent Progress in Applications of Computing to Radiotherapy, 62(11): 4237, 2017
- Burgos, N., Cardoso, M.J., Thielemans, K., Modat, M., Pedemonte, S., Dickson, J., Barnes, A., Ahmed, R., Mahoney, C.J., Schott, J.M., Duncan, J.S., Atkinson, D., Arridge, S.R., Hutton, B.F., and Ourselin, S.: Attenuation Correction Synthesis for Hybrid PET-MR Scanners: Application to Brain Studies. IEEE Transactions on Medical Imaging, 33(12): 2332–2341, 2014. doi:10.1109/TMI.2014.2340135
SASHIMI 2019: A MICCAI 2019 workshop
Building on the successful past three years, SASHIMI continues to provide a state-of-the-art and integrative perspective on simulation and synthesis in medical imaging for the purpose of invigorating research and stimulating new ideas on how to build theoretical links, practical synergies, and best practices between these two research directions.