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Number of items: 17.
Article
Gibson, E;
Li, W;
Sudre, C;
Fidon, L;
Shakir, DI;
Wang, G;
Eaton-Rosen, Z;
... Vercauteren, T; + view all
(2018)
NiftyNet: a deep-learning platform for medical imaging.
Computer Methods and Programs in Biomedicine
, 158
pp. 113-122.
10.1016/j.cmpb.2018.01.025.
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Hu, Y;
Modat, M;
Gibson, E;
Li, W;
Ghavami, N;
Bonmati, E;
Wang, G;
... Vercauteren, T; + view all
(2018)
Weakly-supervised convolutional neural networks for multimodal image registration.
Medical Image Analysis
, 49
pp. 1-13.
10.1016/j.media.2018.07.002.
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Manivannan, S;
Li, W;
Zhang, J;
Trucco, E;
McKenna, SJ;
(2018)
Structure Prediction for Gland Segmentation With Hand-Crafted and Deep Convolutional Features.
IEEE Transactions on Medical Imaging
, 37
(1)
pp. 210-221.
10.1109/TMI.2017.2750210.
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Wang, G;
Li, W;
Zuluaga, MA;
Pratt, R;
Patel, PA;
Aertsen, M;
Doel, T;
... Vercauteren, T; + view all
(2018)
Interactive Medical Image Segmentation using Deep Learning with Image-specific Fine-tuning.
IEEE Transactions on Medical Imaging
, 37
(7)
pp. 1562-1573.
10.1109/TMI.2018.2791721.
(In press).
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Wang, G;
Zuluaga, MA;
Li, W;
Pratt, R;
Patel, PA;
Aertsen, M;
Doel, T;
... Vercauteren, T; + view all
(2019)
DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation.
IEEE Transactions on Pattern Analysis and Machine Intelligence
, 41
(7)
1559 -1572.
10.1109/TPAMI.2018.2840695.
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Proceedings paper
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Bragman, FJS;
Tanno, R;
Eaton-Rosen, Z;
Li, W;
Hawkes, DJ;
Ourselin, S;
Alexander, DC;
... Cardoso, MJ; + view all
(2018)
Uncertainty in Multitask Learning: Joint Representations for Probabilistic MR-only Radiotherapy Planning.
In: Frangi, AF and Schnabel, JA and Davatzikos, C and Alberola-López, C and Fichtinger, G, (eds.)
Medical Image Computing and Computer Assisted Intervention: Proceedings, Part IV.
(pp. pp. 3-11).
Springer: Cham, Switzerland.
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Ebner, M;
Wang, G;
Li, W;
Aertsen, M;
Patel, PA;
Aughwane, R;
Melbourne, A;
... Vercauteren, T; + view all
(2018)
An automated localization, segmentation and reconstruction framework for fetal brain MRI.
In: Frangi, AF and Schnabel, JA and Davatzikos, C and Alberola-López, C and Fichtinger, G, (eds.)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part I.
(pp. pp. 313-320).
Springer: Cham, Switzerland.
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Fidon, L;
Li, W;
Garcia-Peraza-Herrera, LC;
Ekanayake, J;
Kitchen, N;
Ourselin, S;
Vercauteren, T;
(2018)
Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation Using Holistic Convolutional Networks.
In: Crimi, A and Bakas, S and Kuijf, H and Menze, B and Reyes, M, (eds.)
BrainLes 2017: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries.
(pp. pp. 64-76).
Springer: Cham, Switzerland.
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Fidon, L;
Li, W;
Garcia-Peraza-Herrera, LC;
Ekanayake, J;
Kitchen, N;
Ourselin, S;
Vercauteren, T;
(2017)
Scalable multimodal convolutional networks for brain tumour segmentation.
In: Descoteaux, M and Maier-Hein, L and Franz, A and Jannin, P and Collins, D and Duchesne, S, (eds.)
Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017.
(pp. pp. 285-293).
Springer: Cham.
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Garcia Peraza Herrera, LC;
Li, W;
Gruijthuijsen, C;
Devreker, A;
Attilakos, G;
Deprest, J;
Vander Poorten, E;
... Ourselin, S; + view all
(2017)
Real-Time Segmentation of Non-Rigid Surgical Tools based on Deep Learning and Tracking.
In:
Computer-Assisted and Robotic Endoscopy. CARE 2016. Lecture Notes in Computer Science.
(pp. pp. 84-95).
Springer Verlag (Germany): Germany.
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Garcia-Peraza-Herrera, LC;
Li, W;
Fidon, L;
Gruijthuijsen, C;
Devreker, A;
Attilakos, G;
Deprest, J;
... Ourselin, S; + view all
(2017)
ToolNet: Holistically-Nested Real-Time Segmentation of Robotic Surgical Tools.
In: Bicchi, A and Okamura, A, (eds.)
Proceedings of 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
(pp. pp. 5717-5722).
IEEE: USA: New York.
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Kläser, K;
Markiewicz, P;
Ranzini, M;
Li, W;
Modat, M;
Hutton, BF;
Atkinson, D;
... Ourselin, S; + view all
(2018)
Deep Boosted Regression for MR to CT Synthesis.
In: Gooya, A and Goksel, O and Oguz, I and Burgos, N, (eds.)
SASHIMI 2018: Simulation and Synthesis in Medical Imaging: Proceedings.
(pp. pp. 61-70).
Springer: Cham, Switzerland.
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Li, W;
Manivannan, S;
Akbar, S;
Zhang, J;
Trucco, E;
McKenna, SJ;
(2016)
Gland segmentation in colon histology images using hand-crafted features and convolutional neural networks.
In: Kybic, J and Šonka, M, (eds.)
ISBI 2016: 13th International Symposium on Biomedical Imaging: Proceedings.
(pp. pp. 1405-1408).
Institute of Electrical and Electronics Engineers (IEEE)
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Li, W;
Wang, G;
Fidon, L;
Ourselin, S;
Cardoso, MJ;
Vercauteren, T;
(2017)
On the compactness, efficiency, and representation of 3D convolutional networks: Brain parcellation as a pretext task.
In: Niethammer, M and Styner, M and Aylward, S and Zhu, H and Oguz, I and Yap, PT and Shen, D, (eds.)
Information Processing in Medical Imaging: 25th International Conference, IPMI 2017, Boone, NC, USA, June 25-30, 2017, Proceedings.
(pp. pp. 348-360).
Springer: Cham, Switzerland.
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Manivannan, S;
Li, W;
Akbar, S;
Zhang, J;
Trucco, E;
McKenna, SJ;
(2016)
Local structure prediction for gland segmentation.
In: Kybic, J and Šonka, M, (eds.)
ISBI 2016: 13th International Symposium on Biomedical Imaging: Proceedings.
(pp. pp. 799-802).
Institute of Electrical and Electronics Engineers (IEEE)
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Sudre, CH;
Li, W;
Vercauteren, T;
Ourselin, S;
Cardoso, MJ;
(2017)
Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations.
In:
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support.
(pp. pp. 240-248).
Springer Nature: Cham, Switzerland.
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Wang, G;
Li, W;
Ourselin, S;
Vercauteren, T;
(2018)
Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks.
In: Crimi, A and Bakas, S and Kuijf, H and Menze, B and Reyes, M, (eds.)
BrainLes 2017: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries.
(pp. pp. 178-190).
Springer: Cham, Switzerland.
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