| Spinal cord grey matter segmentation challenge F Prados, J Ashburner, C Blaiotta, T Brosch, J Carballido-Gamio, ... Neuroimage 152, 312-329, 2017 | 155 | 2017 |
| Generative diffeomorphic modelling of large MRI data sets for probabilistic template construction C Blaiotta, P Freund, MJ Cardoso, J Ashburner NeuroImage 166, 117-134, 2018 | 40 | 2018 |
| Variational inference for medical image segmentation C Blaiotta, MJ Cardoso, J Ashburner Computer Vision and Image Understanding 151, 14-28, 2016 | 35 | 2016 |
| Learning generative socially aware models of pedestrian motion C Blaiotta IEEE Robotics and Automation Letters 4 (4), 3433-3440, 2019 | 23 | 2019 |
| Relationship between brainstem neurodegeneration and clinical impairment in traumatic spinal cord injury P Grabher, C Blaiotta, J Ashburner, P Freund NeuroImage: Clinical 15, 494-501, 2017 | 17 | 2017 |
| Simultaneous voxel‐wise analysis of brain and spinal cord morphometry and microstructure within the SPM framework M Azzarito, SP Kyathanahally, Y Balbastre, M Seif, C Blaiotta, ... Human brain mapping 42 (1), 220-232, 2021 | 14 | 2021 |
| Microstructural plasticity in nociceptive pathways after spinal cord injury SP Kyathanahally, M Azzarito, J Rosner, VD Calhoun, C Blaiotta, ... Journal of Neurology, Neurosurgery & Psychiatry 92 (8), 863-871, 2021 | 13 | 2021 |
| A probabilistic framework to learn average shaped tissue templates and its application to spinal cord image segmentation C Blaiotta, P Freund, A Curt, J Cardoso, J Ashburner Proceedings of the 24th ISMRM Annual Meeting, 2016 | 11 | 2016 |
| Overcoming shortcut learning in a target domain by generalizing basic visual factors from a source domain P Saranrittichai, CK Mummadi, C Blaiotta, M Munoz, V Fischer European Conference on Computer Vision, 294-309, 2022 | 8 | 2022 |
| Generative diffeomorphic atlas construction from brain and spinal cord MRI data C Blaiotta, P Freund, MJ Cardoso, J Ashburner arXiv preprint arXiv:1707.01342, 2017 | 6 | 2017 |
| Multi-attribute open set recognition P Saranrittichai, CK Mummadi, C Blaiotta, M Munoz, V Fischer DAGM German Conference on Pattern Recognition, 101-115, 2022 | 4 | 2022 |
| Making time-series predictions using a trained decoder model C Blaiotta, S Ziesche US Patent App. 17/348,367, 2021 | 2 | 2021 |
| Movement prediction of pedestrians useful for autonomous driving C Blaiotta US Patent 11,643,106, 2023 | 1 | 2023 |
| Data augmentation for the training of image classifiers C Blaiotta US Patent App. 17/742,778, 2022 | 1 | 2022 |
| Training neural networks with a lesser requirement for labelled training data P Saranrittichai, AMM Delgado, CK Mummadi, C Blaiotta, V Fischer US Patent App. 18/309,335, 2023 | | 2023 |
| Image classifier with lesser requirement for labelled training data P Saranrittichai, AMM Delgado, CK Mummadi, C Blaiotta, V Fischer US Patent App. 17/861,440, 2023 | | 2023 |
| Method for determining an output signal by means of a neural network C Blaiotta, P Katiyar US Patent App. 17/652,132, 2022 | | 2022 |
| Bayesian generative learning of brain and spinal cord templates from neuroimaging datasets C Blaiotta UCL (University College London), 2017 | | 2017 |
| King’s Research Portal F Prados, J Ashburner, C Blaiotta, T Brosch, J Carballido-Gamio, ... NeuroImage 152, 312-329, 2017 | | 2017 |
| Simultaneous Voxel Based Analysis of Brain and Spinal Cord: Application to Spinal Cord Injury Patients M Azzarito, C Blaiotta, J Ashburner, Y Balbastre, SP Kyathanahally, ... | | |
