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Deep Learning for Medical Imaging: Learning Clinically Useful Information from Images

Publications

Differentially Private Graph Neural Networks for Whole-Graph Classification

Auteurs: Tamara T. Mueller, Johannes C. Paetzold, Chinmay Prabhakar, Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis
Publié dans: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, ISSN 1939-3539
Éditeur: IEEE Computer Society
DOI: 10.1109/tpami.2022.3228315

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

Auteurs: Mengyun Qiao; Shuo Wang; Huaqi Qiu; Antonio De Marvao; Declan P. O’Regan; Daniel Rueckert; Wenjia Bai
Publié dans: IEEE Transactions on Medical Imaging, 2023, ISSN 1558-254X
Éditeur: IEEE Computer Society
DOI: 10.1109/tmi.2023.3331982

Enhancing MR image segmentation with realistic adversarial data augmentation

Auteurs: Chen Chen, Chen Qin, Cheng Ouyang, Zeju Li, Shuo Wang, Huaqi Qiu, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert
Publié dans: Medical Image Analysis, 2022, ISSN 1361-8415
Éditeur: Elsevier BV
DOI: 10.1016/j.media.2022.102597

Unrolled and rapid motion-compensated reconstruction for cardiac CINE MRI

Auteurs: Jiazhen Pan; Manal Hamdi; Wenqi Huang; Kerstin Hammernik; Thomas Kuestner; Daniel Rueckert
Publié dans: Medical Image Analysis, 2024, ISSN 1361-8415
Éditeur: Elsevier BV
DOI: 10.1016/j.media.2023.103017

CortexODE: Learning Cortical Surface Reconstruction by Neural ODEs

Auteurs: Qiang Ma, Liu Li, Emma C Robinson, Bernhard Kainz, Daniel Rueckert, Amir Alansary
Publié dans: IEEE Transactions on Medical Imaging, 2022, ISSN 0278-0062
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2022.3206221

DeepMesh: Mesh-based Cardiac Motion Tracking using Deep Learning

Auteurs: Qingjie Meng; Wenjia Bai; Declan P O’Regan; Daniel Rueckert
Publié dans: IEEE Transactions on Medical Imaging, 2023, ISSN 0278-0062
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2023.3340118

Causality-inspired Single-source Domain Generalization for Medical Image Segmentation

Auteurs: Cheng Ouyang, Chen Chen, Surui Li, Zeju Li, Chen Qin, Wenjia Bai, Daniel Rueckert
Publié dans: IEEE Transactions on Medical Imaging, 2022, ISSN 0278-0062
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmi.2022.3224067

Self-Supervised Motion-Corrected Image Reconstruction Network for 4D Magnetic Resonance Imaging of the Body Trunk

Auteurs: Thomas Küstner, Jiazhen Pan, Christopher Gilliam, Haikun Qi, Gastao Cruz, Kerstin Hammernik, Thierry Blu, Daniel Rueckert, René Botnar, Claudia Prieto and Sergios Gatidis
Publié dans: APSIPA Transactions on Signal and Information Processing, 2022, ISSN 2048-7703
Éditeur: Cambridge University Press
DOI: 10.1561/116.00000039

Neural Implicit k-Space for Binning-Free Non-Cartesian Cardiac MR Imaging

Auteurs: Wenqi Huang, Hongwei Bran Li, Jiazhen Pan, Gastao Cruz, Daniel Rueckert, Kerstin Hammernik
Publié dans: Information Processing in Medical Imaging, 2023
Éditeur: Springer
DOI: 10.1007/978-3-031-34048-2_42

Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations

Auteurs: Julian McGinnis, Suprosanna Shit, Hongwei Bran Li, Vasiliki Sideri-Lampretsa, Robert Graf, Maik Dannecker, Jiazhen Pan, Nil Stolt-Ansó, Mark Mühlau, Jan S. Kirschke, Daniel Rueckert & Benedikt Wiestler
Publié dans: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023, 2023
Éditeur: Springer
DOI: 10.1007/978-3-031-43993-3_17

Learning-Based and Unrolled Motion-Compensated Reconstruction for Cardiac MR CINE Imaging

Auteurs: Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik
Publié dans: Medical Image Computing and Computer Assisted Intervention – MICCAI 2022, 2022
Éditeur: Springer
DOI: 10.1007/978-3-031-16446-0_65

Propagation and Attribution of Uncertainty in Medical Imaging Pipelines

Auteurs: Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis
Publié dans: International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023
Éditeur: Springer
DOI: 10.1007/978-3-031-44336-7_1

Exploiting Segmentation Labels and Representation Learning to Forecast Therapy Response of PDAC Patients

Auteurs: Ziller, Alexander; Erdur, Ayhan Can; Jungmann, Friederike; Rueckert, Daniel; Braren, Rickmer; Kaissis, Georgios
Publié dans: IEEE International Symposium on Biomedical Imaging, 2023
Éditeur: IEEE Computer Society
DOI: 10.1109/isbi53787.2023.10230324

Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimation

Auteurs: Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik
Publié dans: International Workshop on Machine Learning for Medical Image Reconstruction, 2021
Éditeur: Springer
DOI: 10.1007/978-3-030-88552-6_2

Global k-Space Interpolation for Dynamic MRI Reconstruction Using Masked Image Modeling

Auteurs: Jiazhen Pan, Suprosanna Shit, Özgün Turgut, Wenqi Huang, Hongwei Bran Li, Nil Stolt-Ansó, Thomas Küstner, Kerstin Hammernik, Daniel Rueckert
Publié dans: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023, 2023
Éditeur: Springer
DOI: 10.1007/978-3-031-43999-5_22

Body Fat Estimation from Surface Meshes Using Graph Neural Networks.

Auteurs: Tamara T. Mueller, Siyu Zhou, Sophie Starck, Friederike Jungmann, Alexander Ziller, Orhun Aksoy, Danylo Movchan, Rickmer Braren, Georgios Kaissis, Daniel Rueckert
Publié dans: Shape in Medical Imaging, 2023
Éditeur: Springer
DOI: 10.1007/978-3-031-46914-5_9

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