Reading group meetings on Fetal MRI regularly take place about every two weeks and are held on a rotating basis at the Imperial College London and University College London. People interested in joining are always welcome and if you think that this reading group will also benefit your research, then simply drop an email to Michael Ebner (UCL) or Amir Alansary (Imperial College London) for further information.
April 25, 2017 at UCL:
Tourbier, S. et al., 2015. An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization. NeuroImage, 118, pp.1–14.
April 6, 2017 at Imperial College:
Turk, E.A. et al., 2017. Spatiotemporal Alignment of In Utero BOLD-MRI Series. Journal of Magnetic Resonance maging, pp.1–10.
March 21, 2017 at UCL:
Kuklisova-Murgasova, M. et al., 2013. Registration of 3D fetal neurosonography and MRI. Medical Image Analysis, 17(8), pp.1137–1150.
February 28, 2017 at Imperial College:
Marami, B. et al., 2016. Motion-Robust Diffusion-Weighted Brain MRI Reconstruction Through Slice-Level Registration-Based Motion Tracking. IEEE Transactions on Medical Imaging, 35(10), pp.2258–2269.
January 31, 2017 at UCL:
Caballero, J. et al., 2016. Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation. arXiv:1611.05250.
January 10, 2017 at Imperial College:
Mnih, V. et al., 2015. Human-level control through deep reinforcement learning. Nature, 518(7540), pp.529–533.
- December 20, 2016 at UCL:
Jaderberg, M. et al., 2015. Spatial Transformer Networks. In Advances in Neural Information Processing Systems. Curran Associates, Inc., pp. 2017–2025.
- November 29, 2016 at Imperial College:
Pathak, D. et al., 2015. Constrained Convolutional Neural Networks for Weakly Supervised Segmentation. Proceedings of the IEEE International Conference on Computer Vision.
- November 15, 2016 at UCL:
- September 27, 2016 at Imperial College:
Kamnitsas, K. et al., 2016. Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation. arXiv:1603.05959.
- September 16, 2016 at UCL:
Kuklisova-Murgasova, M. et al., 2012. Reconstruction of fetal brain MRI with intensity matching and complete outlier removal. Medical Image Analysis, 16(8), pp.1550–1564.
- August 30, 2016 at Imperial College:
Ball, G. et al., 2013. Development of cortical microstructure in the preterm human brain. Proceedings of the National Academy of Sciences, 110(23), pp.9541–9546.
- August 9, 2016 at UCL:
Keraudren, K. et al., 2015. Automated Localization of Fetal Organs in MRI Using Random Forests with Steerable Features. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. Lecture Notes in Computer Science. Springer International Publishing, pp. 620–627.
- July 11, 2016 at UCL and July 26, 2016 at Imperial College:
Gholipour, A. et al., 2010. Robust Super-Resolution Volume Reconstruction From Slice Acquisitions: Application to Fetal Brain MRI. IEEE Transactions on Medical Imaging, 29(10), pp.1739–1758.
June 27, 2016 at Imperial College:
- Habas, P.A. et al., 2010. A spatiotemporal atlas of MR intensity, tissue probability and shape of the fetal brain with application to segmentation. NeuroImage, 53(2), pp.460–470.
- Habas, P.A. et al., 2009. A Spatio-temporal Atlas of the Human Fetal Brain with Application to Tissue Segmentation. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009. Springer Berlin Heidelberg, pp. 289–296.
June 13, 2016 at UCL:
- Kim, K. et al., 2010. Intersection Based Motion Correction of Multislice MRI for 3-D in Utero Fetal Brain Image Formation. IEEE Transactions on Medical Imaging, 29(1):146–158.
- Kim, K. et al., 2008. Intersection based registration of slice stacks to form 3D images of the human fetal brain. In 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1167–1170. IEEE.
- May 31, 2016 at Imperial College:
- Keraudren, K. et al., 2014. Automated fetal brain segmentation from 2D MRI slices for motion correction. NeuroImage, 101:633–643.
- Keraudren, K. et al., 2013. Localisation of the Brain in Fetal MRI Using Bundled SIFT Features. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, volume 8149 LNCS, pp.582–589.
- May 10, 2016 at UCL:
Jiang, S. et al., 2007. MRI of Moving Subjects Using Multislice Snapshot Images With Volume Reconstruction (SVR): Application to Fetal, Neonatal, and Adult Brain Studies. IEEE transactions on medical imaging, 26(7):967–80.
- April 29, 2016 at Imperial College:
- Ison, M. et al., 2012. Fully Automated Brain Extraction and Orientation in Raw Fetal MRI. Workshop on Paediatric and Perinatal Imaging, MICCAI.
- Anquez, J. et al., 2009. Automatic segmentation of head structures on fetal MRI. In 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.109–112. IEEE.
- April 15, 2016 at UCL:
- Rousseau, F. et al., 2006. Registration-Based Approach for Reconstruction of High-Resolution In Utero Fetal MR Brain Images. Academic Radiology, 13(9):1072–1081.
- Rousseau, F. et al.,2005. A Novel Approach to High Resolution Fetal Brain MR Imaging. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005, volume 8, pages 548–555. Springer.