Author of the publication

Hierarchical Brain Parcellation with Uncertainty.

, , , , , , and . UNSURE/GRAIL@MICCAI, volume 12443 of Lecture Notes in Computer Science, page 23-31. Springer, (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

 

Other publications of authors with the same name

ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping., , , , , and . NeurIPS, (2020)Unsupervised Heteromodal Physics-Informed Representation of MRI Data: Tackling Data Harmonisation, Imputation and Domain Shift., , , , , and . SASHIMI@MICCAI, volume 14288 of Lecture Notes in Computer Science, page 53-63. Springer, (2023)Generating multi-pathological and multi-modal images and labels for brain MRI., , , , , , and . Medical Image Anal., (2024)Self-Supervised Anomaly Detection from Anomalous Training Data via Iterative Latent Token Masking., , , , , , , , and . ICCV (Workshops), page 2394-2402. IEEE, (2023)Cross Attention Transformers for Multi-modal Unsupervised Whole-Body PET Anomaly Detection., , , , , , and . DGM4MICCAI@MICCAI, volume 13609 of Lecture Notes in Computer Science, page 14-23. Springer, (2022)ICAM-Reg: Interpretable Classification and Regression With Feature Attribution for Mapping Neurological Phenotypes in Individual Scans., , , , , , , , , and 1 other author(s). IEEE Trans. Medical Imaging, 42 (4): 959-970 (April 2023)Unsupervised Brain Anomaly Detection and Segmentation with Transformers., , , , , , and . MIDL, volume 143 of Proceedings of Machine Learning Research, page 596-617. PMLR, (2021)Transformer-based out-of-distribution detection for clinically safe segmentation., , , , , , , , , and 2 other author(s). MIDL, volume 172 of Proceedings of Machine Learning Research, page 457-476. PMLR, (2022)Denoising diffusion models for out-of-distribution detection., , , , , and . CVPR Workshops, page 2948-2957. IEEE, (2023)Unsupervised 3D Out-of-Distribution Detection with Latent Diffusion Models., , , , , , , , , and 1 other author(s). MICCAI (1), volume 14220 of Lecture Notes in Computer Science, page 446-456. Springer, (2023)