Browse by UCL people
Group by: Type | Date
Number of items: 15.
Article
Ashburner, J;
Brudfors, M;
Bronik, K;
Balbastre, Y;
(2019)
An algorithm for learning shape and appearance models without annotations.
Medical Image Analysis
, 55
pp. 197-215.
10.1016/j.media.2019.04.008.
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Balbastre, Y;
Brudfors, M;
Azzarito, M;
Lambert, C;
Callaghan, MF;
Ashburner, J;
(2021)
Model-based multi-parameter mapping.
Medical Image Analysis
, 73
, Article 102149. 10.1016/j.media.2021.102149.
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Tso, AR;
Brudfors, M;
Danno, D;
Grangeon, L;
Cheema, S;
Matharu, M;
Nachev, P;
(2020)
Machine phenotyping of cluster headache and its response to verapamil.
Brain
10.1093/brain/awaa388.
(In press).
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Yan, Yu;
Balbastre, Yaël;
Brudfors, Mikael;
Ashburner, John;
(2022)
Factorisation-Based Image Labelling.
Frontiers in Neuroscience
, 15
, Article 818604. 10.3389/fnins.2021.818604.
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Proceedings paper
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Balbastre, Y;
Brudfors, M;
Azzarito, M;
Lambert, C;
Callaghan, MF;
Ashburner, J;
(2020)
Joint Total Variation ESTATICS for Robust Multi-parameter Mapping.
In: Martel, A and Abolmaesumi, P and Stoyanov, D and Mateus, D and Zuluaga, M and Zhou, SK and Racoceanu, D and Joskowicz, L, (eds.)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020.
(pp. pp. 53-63).
Springer: Lima, Peru.
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Balbastre, Y;
Brudfors, M;
Bronik, K;
Ashburner, J;
(2018)
Diffeomorphic brain shape modelling using Gauss-Newton optimisation.
In: Frangi, AF and Schnabel, JA and Davatzikos, C and Alberola-López, C, (eds.)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018.
(pp. pp. 862-870).
Springer: Cham, Switzerland.
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Brudfors, M;
Balbastre, Y;
Ashburner, J;
Rees, G;
Nachev, P;
Ourselin, S;
Cardoso, MJ;
(2021)
An MRF-UNet Product of Experts for Image Segmentation.
In:
Proceedings of Machine Learning Research.
(pp. pp. 48-59).
Proceedings of Machine Learning Research (PMLR): Lübeck, Germany.
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Brudfors, M;
Ashburner, J;
Nachev, P;
Balbastre, Y;
(2019)
Empirical bayesian mixture models for medical image translation.
In:
Simulation and Synthesis in Medical Imaging.
(pp. pp. 1-12).
Springer: Cham, Switzerland.
(In press).
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Brudfors, M;
Balbastre, Y;
Ashburner, J;
(2020)
Groupwise Multimodal Image Registration Using Joint Total Variation.
In:
Medical Image Understanding and Analysis.
(pp. pp. 184-194).
Springer: Cham, Switzerland.
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Brudfors, M;
Balbastre, Y;
Ashburner, J;
(2019)
Nonlinear Markov Random Fields Learned via Backpropagation.
In: Chung, A.C.S. and Gee, J.C. and Yushkevich, P.A. and Bao, S., (eds.)
Proceedings of the 26th International Conference on Information Processing in Medical Imaging (IPMI 2019).
(pp. pp. 805-817).
Springer: Cham, Switzerland.
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Brudfors, M;
Balbastre, Y;
Flandin, G;
Nachev, P;
Ashburner, J;
(2020)
Flexible Bayesian Modelling for Nonlinear Image Registration.
In: Martel, A and Abolmaesumi, P and Stoyanov, D and Mateus, D and ZuluagaM, M and Zhou, SK and Racoceanu, D and Joskowicz, L, (eds.)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020.
(pp. pp. 253-263).
Springer: Lima, Peru.
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Brudfors, M;
Balbastre, Y;
Nachev, P;
Ashburner, J;
(2018)
MRI super-resolution using multi-channel total variation.
In: Nixon, M and Mahmoodi, S and Zwiggelaar, R, (eds.)
Medical Image Understanding and Analysis: 22nd Conference, MIUA 2018, Southampton, UK, July 9-11, 2018, Proceedings.
(pp. pp. 217-228).
Springer: Cham, Switzerland.
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Mihalik, A;
Brudfors, M;
Robu, M;
Ferreira, FS;
Lin, H;
Rau, A;
Wu, T;
... Oxtoby, NP; + view all
(2019)
ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Fluid Intelligence Scores from Structural MRI Using Probabilistic Segmentation and Kernel Ridge Regression.
In: Pohl, K and Thompson, W and Adeli, E and Linguraru, M, (eds.)
Adolescent Brain Cognitive Development Neurocognitive Prediction. ABCD-NP 2019. Lecture Notes in Computer Science.
(pp. pp. 133-142).
Springer: Cham.
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Oxtoby, NP;
Ferreira, FS;
Mihalik, A;
Wu, T;
Brudfors, M;
Lin, H;
Rau, A;
... Mourão-Miranda, J; + view all
(2019)
ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Residual Fluid Intelligence Scores from Cortical Grey Matter Morphology.
In: Pohl, K and Thompson, W and Adeli, E and Linguraru, M, (eds.)
Adolescent Brain Cognitive Development Neurocognitive Prediction. ABCD-NP 2019. Lecture Notes in Computer Science, vol 11791.
(pp. pp. 114-123).
Springer: Cham.
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Thesis
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Brudfors, Mikael;
(2020)
Generative Models for Preprocessing of Hospital Brain Scans.
Doctoral thesis (Ph.D), UCL (University College London).
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