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Antonio Criminisi

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

Dec 10, 2018
Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

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* Submitted to SPIE Journal of Medical Imaging

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Semi-Supervised Learning via Compact Latent Space Clustering

Jul 29, 2018
Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori

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* Presented as a long oral in ICML 2018. Post-conference camera ready

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3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context

Jul 23, 2018
Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

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* Submitted to the journal Computerized Medical Imaging and Graphics

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Autofocus Layer for Semantic Segmentation

Jun 11, 2018
Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison Cottrell, Antonio Criminisi, Aditya Nori

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* Published on MICCAI 2018

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Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution

May 30, 2017
Ryutaro Tanno, Daniel E. Worrall, Aurobrata Ghosh, Enrico Kaden, Stamatios N. Sotiropoulos, Antonio Criminisi, Daniel C. Alexander

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* Accepted paper at MICCAI 2017

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Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups

Nov 30, 2016
Yani Ioannou, Duncan Robertson, Roberto Cipolla, Antonio Criminisi

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* Updated full version of paper, in full letter paper two-column paper. Includes many textual changes, updated CIFAR10 results, and new analysis of inter/intra-layer correlation

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