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Daniel Rueckert
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Equivariant Differentially Private Deep Learning


Jan 30, 2023
Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis

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CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy


Jan 30, 2023
Mengyun Qiao, Shuo Wang, Huaqi Qiu, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert, Wenjia Bai

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Clustering disease trajectories in contrastive feature space for biomarker discovery in age-related macular degeneration


Jan 11, 2023
Robbie Holland, Oliver Leingang, Christopher Holmes, Philipp Anders, Johannes C. Paetzold, Rebecca Kaye, Sophie Riedl, Hrvoje Bogunović, Ursula Schmidt-Erfurth, Lars Fritsche, Hendrik P. N. Scholl, Sobha Sivaprasad, Andrew J. Lotery, Daniel Rueckert, Martin J. Menten

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* Submitted to IPMI2023 
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Approaching Peak Ground Truth


Dec 31, 2022
Florian Kofler, Johannes Wahle, Ivan Ezhov, Sophia Wagner, Rami Al-Maskari, Emilia Gryska, Mihail Todorov, Christina Bukas, Felix Meissen, Tingying Peng, Ali Ertürk, Daniel Rueckert, Rolf Heckemann, Jan Kirschke, Claus Zimmer, Benedikt Wiestler, Bjoern Menze, Marie Piraud

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* 7pages, 2 figures 
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Neural Implicit k-Space for Binning-free Non-Cartesian Cardiac MR Imaging


Dec 16, 2022
Wenqi Huang, Hongwei Li, Gastao Cruz, Jiazhen Pan, Daniel Rueckert, Kerstin Hammernik

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A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images


Dec 03, 2022
Hongwei Bran Li, Chinmay Prabhakar, Suprosanna Shit, Johannes Paetzold, Tamaz Amiranashvili, Jianguo Zhang, Daniel Rueckert, Juan Eugenio Iglesias, Benedikt Wiestler, Bjoern Menze

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* under review 
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How Do Input Attributes Impact the Privacy Loss in Differential Privacy?


Nov 18, 2022
Tamara T. Mueller, Stefan Kolek, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Daniel Rueckert, Georgios Kaissis

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The Role of Local Alignment and Uniformity in Image-Text Contrastive Learning on Medical Images


Nov 14, 2022
Philip Müller, Georgios Kaissis, Daniel Rueckert

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* NeurIPS 2022 Workshop: Self-Supervised Learning - Theory and Practice 
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Exploiting segmentation labels and representation learning to forecast therapy response of PDAC patients


Nov 08, 2022
Alexander Ziller, Ayhan Can Erdur, Friederike Jungmann, Daniel Rueckert, Rickmer Braren, Georgios Kaissis

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Automated analysis of diabetic retinopathy using vessel segmentation maps as inductive bias


Oct 28, 2022
Linus Kreitner, Ivan Ezhov, Daniel Rueckert, Johannes C. Paetzold, Martin J. Menten

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* Submission for MICCAI 2022 Diabetic Retinopathy Analysis Challenge (DRAC) Proceedings, DOI: 10.5281/zenodo.6362349 
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