| Automated segmentation of the hypothalamus and associated subunits in brain MRI B Billot, M Bocchetta, E Todd, AV Dalca, JD Rohrer, JE Iglesias Neuroimage 223, 117287, 2020 | 67 | 2020 |
| A Learning Strategy for Contrast-agnostic MRI Segmentation B Billot, D Greve, K Van Leemput, B Fischl, JE Iglesias, AV Dalca Proceedings of the Third Conference on Medical Imaging with Deep Learning …, 2020 | 67 | 2020 |
| SynthMorph: learning contrast-invariant registration without acquired images M Hoffmann, B Billot, DN Greve, JE Iglesias, B Fischl, AV Dalca IEEE transactions on medical imaging 41 (3), 543-558, 2021 | 57* | 2021 |
| Joint super-resolution and synthesis of 1 mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast JE Iglesias, B Billot, Y Balbastre, A Tabari, J Conklin, RG González, ... Neuroimage 237, 118206, 2021 | 43 | 2021 |
| SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining B Billot, DN Greve, O Puonti, A Thielscher, K Van Leemput, B Fischl, ... Medical Image Analysis, 102789, 2023 | 36* | 2023 |
| Image synthesis with a convolutional capsule generative adversarial network C Bass, T Dai, B Billot, K Arulkumaran, A Creswell, C Clopath, V De Paola, ... | 26 | 2019 |
| Partial volume segmentation of brain MRI scans of any resolution and contrast B Billot, E Robinson, AV Dalca, JE Iglesias Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 22 | 2020 |
| Deep reinforcement learning for subpixel neural tracking T Dai, M Dubois, K Arulkumaran, J Campbell, C Bass, B Billot, F Uslu, ... International conference on medical imaging with deep learning, 130-150, 2019 | 18 | 2019 |
| A deep learning toolbox for automatic segmentation of subcortical limbic structures from MRI images DN Greve, B Billot, D Cordero, A Hoopes, M Hoffmann, AV Dalca, B Fischl, ... Neuroimage 244, 118610, 2021 | 16 | 2021 |
| Quantitative brain morphometry of portable low-field-strength MRI using super-resolution machine learning JE Iglesias, R Schleicher, S Laguna, B Billot, P Schaefer, B McKaig, ... Radiology, 220522, 2022 | 9* | 2022 |
| SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry JE Iglesias, B Billot, Y Balbastre, C Magdamo, SE Arnold, S Das, ... Science advances 9 (5), eadd3607, 2023 | 5 | 2023 |
| Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets B Billot, C Magdamo, Y Cheng, SE Arnold, S Das, JE Iglesias Proceedings of the National Academy of Sciences 120 (9), e2216399120, 2023 | 4 | 2023 |
| Robust segmentation of brain mri in the wild with hierarchical cnns and no retraining B Billot, C Magdamo, SE Arnold, S Das, JE Iglesias Medical Image Computing and Computer Assisted Intervention–MICCAI 2022: 25th …, 2022 | 4 | 2022 |
| Joint segmentation of multiple sclerosis lesions and brain anatomy in MRI scans of any contrast and resolution with CNNs B Billot, S Cerri, K Van Leemput, AV Dalca, JE Iglesias 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1971-1974, 2021 | 4 | 2021 |
| Super-resolution of portable low-field MRI in real scenarios: integration with denoising and domain adaptation S Laguna, R Schleicher, B Billot, P Schaefer, B McKaig, JN Goldstein, ... Medical Imaging with Deep Learning, 2022 | 2 | 2022 |
| In vivo hypothalamic regional volumetry across the frontotemporal dementia spectrum NL Shapiro, EG Todd, B Billot, DM Cash, JE Iglesias, JD Warren, ... NeuroImage: Clinical 35, 103084, 2022 | 1 | 2022 |
| Synthesis of High-Resolution Research-Quality MRI Data from Clinical MRI Data in Patients with COVID-19 RJ Cali, HJ Freeman, B Billot, ME Barra, D Fischer, WR Sanders, ... medRxiv, 2021.11. 25.21266090, 2021 | 1 | 2021 |
| Domain-agnostic segmentation of thalamic nuclei from joint structural and diffusion MRI HFJ Tregidgo, S Soskic, MD Olchanyi, J Althonayan, B Billot, C Maffei, ... arXiv preprint arXiv:2305.03413, 2023 | | 2023 |
| Brain growth charts of" clinical controls" for quantitative analysis of clinically acquired brain MRI JM Schabdach, JE Schmitt, S Sotardi, A Vossough, S Andronikou, ... medRxiv, 2023.01. 13.23284533, 2023 | | 2023 |
| Bridging generative models and Convolutional Neural Networks for domain-agnostic segmentation of brain MRI BPM Billot UCL (University College London), 2022 | | 2022 |
Juan Eugenio IglesiasMassachusetts General Hospital & Harvard Medical School / MIT / UCLVerified email at mgh.harvard.edu
