Imperial College London / The Imperial College of Science, Technology and Medicine

University / College


Location: London, United Kingdom (GB) GB

ISNI: 0000000121138111

ROR: https://ror.org/041kmwe10

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Types of publications

Journal article
Book chapter / Article in edited volumes
Authored book
Translation
Thesis
Edited Volume
Conference contribution
Other publication type
Unpublished / Preprint

Publication year

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To

Abstract

Journal

Fluorescence enhancement of Er3+-ions using reverse hybrid plasmonic nano-focusing (2022) Güsken NA, Fu M, Zapf M, Nielsen MP, Dichtl P, Roder R, Maier SA, et al. Conference contribution Quantum photo-thermodynamics on a programmable photonic quantum processor (2022) Anguita MC, Somhorst FH, van der Meer R, Schadow R, Snijders HJ, de Goede M, Kassenberg B, et al. Conference contribution Pure-state certification by undoing Hamiltonian evolution leading to local thermalization (2022) Correa Anguita M, Somhorst FH, van der Meer R, Schadow R, Snijders HJ, de Goede M, Kassenberg B, et al. Conference contribution Learning a Model-Driven Variational Network for Deformable Image Registration (2022) Jia X, Thorley A, Chen W, Qiu H, Shen L, Styles IB, Chang HJ, et al. Journal article Developing and validating a multivariable prediction model which predicts progression of intermediate to late age-related macular degeneration—the PINNACLE trial protocol (2022) Sutton J, Menten MJ, Riedl S, Bogunovic H, Leingang O, Anders P, Hagag AM, et al. Journal article Faster Diffusion Cardiac MRI with Deep Learning-Based Breath Hold Reduction (2022) Tanzer M, Ferreira P, Scott A, Khalique Z, Dwornik M, Pennell D, Yang G, et al. Conference contribution MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation (2022) Chen C, Li Z, Ouyang C, Sinclair M, Bai W, Rueckert D Conference contribution Embedding Gradient-Based Optimization in Image Registration Networks (2022) Qiu H, Hammernik K, Qin C, Chen C, Rueckert D Conference contribution Mesh-Based 3D Motion Tracking in Cardiac MRI Using Deep Learning (2022) Meng Q, Bai W, Liu T, O'Regan DP, Rueckert D Conference contribution Can Collaborative Learning Be Private, Robust and Scalable? (2022) Usynin D, Klause H, Paetzold JC, Rueckert D, Kaissis G Conference contribution