Julia A. Schnabel

ORCID

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 172

Top Venues

Publications

Stefan M. Fischer, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel
Mask the Unknown: Assessing Different Strategies to Handle Weak Annotations in the MICCAI2023 Mediastinal Lymph Node Quantification Challenge. CoRR (2024)
Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel
Diffusion Models with Implicit Guidance for Medical Anomaly Detection. CoRR (2024)
Valentin Koch, Sophia J. Wagner, Salome Kazeminia, Ece Sancar, Matthias Hehr, Julia A. Schnabel, Tingying Peng, Carsten Marr
DinoBloom: A Foundation Model for Generalizable Cell Embeddings in Hematology. CoRR (2024)
Fryderyk Victor Kögl, Anna Reithmeir, Vasiliki Sideri-Lampretsa, Inês Machado, Rickmer Braren, Daniel Rückert, Julia A. Schnabel, Veronika A. Zimmer
General Vision Encoder Features as Guidance in Medical Image Registration. CoRR (2024)
Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel
Towards Universal Unsupervised Anomaly Detection in Medical Imaging. CoRR (2024)
Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik, Daniel Rueckert, Christine Preibisch, Dimitrios C. Karampinos, Julia A. Schnabel
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review. IEEE Trans. Medical Imaging 43 (2) (2024)
Richard Osuala, Daniel Lang, Preeti Verma, Smriti Joshi, Apostolia Tsirikoglou, Grzegorz Skorupko, Kaisar Kushibar, Lidia Garrucho, Walter H. L. Pinaya, Oliver Díaz, Julia A. Schnabel, Karim Lekadir
Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models. CoRR (2024)
Richard Osuala, Daniel M. Lang, Anneliese Riess, Georgios Kaissis, Zuzanna Szafranowska, Grzegorz Skorupko, Oliver Díaz, Julia A. Schnabel, Karim Lekadir
Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data. CoRR (2024)
Maxime Di Folco, Cosmin I. Bercea, Julia A. Schnabel
Interpretable Representation Learning of Cardiac MRI via Attribute Regularization. CoRR (2024)
Anna Reithmeir, Lina Felsner, Rickmer Braren, Julia A. Schnabel, Veronika A. Zimmer
Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration. CoRR (2024)
Benedikt Roth, Valentin Koch, Sophia J. Wagner, Julia A. Schnabel, Carsten Marr, Tingying Peng
Low-resource finetuning of foundation models beats state-of-the-art in histopathology. CoRR (2024)
Veronika Spieker, Hannah Eichhorn, Jonathan K. Stelter, Wenqi Huang, Rickmer F. Braren, Daniel Rückert, Francisco Sahli Costabal, Kerstin Hammernik, Claudia Prieto, Dimitrios C. Karampinos, Julia A. Schnabel
Self-Supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representation. CoRR (2024)
Jack Highton, Quok Zong Chong, Samuel Finestone, Arian Beqiri, Julia A. Schnabel, Kanwal K. Bhatia
Robustness Testing of Black-Box Models Against CT Degradation Through Test-Time Augmentation. CoRR (2024)
Inês Prata Machado, Anna Reithmeir, Fryderyk Victor Kögl, Leonardo Rundo, Gabriel Funingana, Marika Reinius, Gift Mungmeeprued, Zeyu Gao, Cathal McCague, Eric Kerfoot, Ramona Woitek, Evis Sala, Yangming Ou, James D. Brenton, Julia A. Schnabel, Mireia Crispin
A Self-Supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer. CoRR (2024)
Tomás Chobola, Yu Liu, Hanyi Zhang, Julia A. Schnabel, Tingying Peng
Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations. CoRR (2024)
Varsha Raveendran, Veronika Spieker, Rickmer F. Braren, Dimitrios C. Karampinos, Veronika A. Zimmer, Julia A. Schnabel
Segmentation-guided Medical Image Registration - Quality Awareness using Label Noise Correctionn. Bildverarbeitung für die Medizin (2024)
Johannes Kiechle, Daniel M. Lang, Stefan M. Fischer, Lina Felsner, Jan C. Peeken, Julia A. Schnabel
Graph Neural Networks: A suitable Alternative to MLPs in Latent 3D Medical Image Classification? CoRR (2024)
Reza Nasirigerdeh, Nader Razmi, Julia A. Schnabel, Daniel Rueckert, Georgios Kaissis
Machine Unlearning for Medical Imaging. CoRR (2024)
Stefan M. Fischer, Lina Felsner, Richard Osuala, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel
Progressive Growing of Patch Size: Resource-Efficient Curriculum Learning for Dense Prediction Tasks. CoRR (2024)
Josh Stein, Maxime Di Folco, Julia A. Schnabel
Influence of Prompting Strategies on Segment Anything Model (SAM) for Short-axis Cardiac MRI Segmentation. Bildverarbeitung für die Medizin (2024)
Deniz Daum, Richard Osuala, Anneliese Riess, Georgios Kaissis, Julia A. Schnabel, Maxime Di Folco
On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion Models. CoRR (2024)
Inês Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Ihsane Olakorede, Ilkay Öksüz, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King
A Deep Learning-Based Integrated Framework for Quality-Aware Undersampled Cine Cardiac MRI Reconstruction and Analysis. IEEE Trans. Biomed. Eng. 71 (3) (2024)
Mehmet Yigit Avci, Emily Chan, Veronika A. M. Zimmer, Daniel Rueckert, Benedikt Wiestler, Julia A. Schnabel, Cosmin I. Bercea
Unsupervised Analysis of Alzheimer's Disease Signatures using 3D Deformable Autoencoders. CoRR (2024)
Jun Li, Cosmin I. Bercea, Philip Müller, Lina Felsner, Suhwan Kim, Daniel Rueckert, Benedikt Wiestler, Julia A. Schnabel
Multi-Image Visual Question Answering for Unsupervised Anomaly Detection. CoRR (2024)
Malek Ben Alaya, Daniel M. Lang, Benedikt Wiestler, Julia A. Schnabel, Cosmin I. Bercea
MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRI. CoRR (2024)
Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik, Daniel Rueckert, Christine Preibisch, Dimitrios C. Karampinos, Julia A. Schnabel
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review. CoRR (2023)
Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection. MICCAI (5) (2023)
Jeronimo Carvajal Maldonado, Lorenz Lamm, Ye Liu, Yu Liu, Ricardo D. Righetto, Julia A. Schnabel, Tingying Peng
F2FD: Fourier Perturbations for Denoising Cryo-Electron Tomograms and Comparison to Established Approaches. ISBI (2023)
Hannah Eichhorn, Kerstin Hammernik, Veronika Spieker, Samira M. Epp, Daniel Rueckert, Christine Preibisch, Julia A. Schnabel
Physics-Aware Motion Simulation For T2*-Weighted Brain MRI. SASHIMI@MICCAI (2023)
Veronika Spieker, Wenqi Huang, Hannah Eichhorn, Jonathan K. Stelter, Kilian Weiss, Veronika A. Zimmer, Rickmer F. Braren, Dimitrios C. Karampinos, Kerstin Hammernik, Julia A. Schnabel
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space. CoRR (2023)
Daniel M. Lang, Eli Schwartz, Cosmin I. Bercea, Raja Giryes, Julia A. Schnabel
Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI. CaPTion@MICCAI (2023)
Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel
Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening. MIDL (2023)
Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection. CoRR (2023)
Veronika Spieker, Wenqi Huang, Hannah Eichhorn, Jonathan K. Stelter, Kilian Weiss, Veronika A. Zimmer, Rickmer F. Braren, Dimitrios C. Karampinos, Kerstin Hammernik, Julia A. Schnabel
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space. DGM4MICCAI (2023)
Maxime Di Folco, Cosmin I. Bercea, Julia A. Schnabel
Attribute Regularized Soft Introspective Variational Autoencoder for Interpretable Cardiac Disease Classification. CoRR (2023)
Martin J. Menten, Johannes C. Paetzold, Veronika A. Zimmer, Suprosanna Shit, Ivan Ezhov, Robbie Holland, Monika Probst, Julia A. Schnabel, Daniel Rueckert
A skeletonization algorithm for gradient-based optimization. ICCV (2023)
Cosmin I. Bercea, Esther Puyol-Antón, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel, Andrew P. King
Bias in Unsupervised Anomaly Detection in Brain MRI. CLIP/FAIMI/EPIMI@MICCAI (2023)
Veronika A. Zimmer, Alberto Gómez, Emily Skelton, Robert Wright, Gavin Wheeler, Shujie Deng, Nooshin Ghavami, Karen Lloyd, Jacqueline Matthew, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel
Placenta segmentation in ultrasound imaging: Addressing sources of uncertainty and limited field-of-view. Medical Image Anal. 83 (2023)
Robert Wright, Alberto Gómez, Veronika A. Zimmer, Nicolas Toussaint, Bishesh Khanal, Jacqueline Matthew, Emily Skelton, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel
Fast fetal head compounding from multi-view 3D ultrasound. Medical Image Anal. 89 (2023)
Cosmin I. Bercea, Michael Neumayr, Daniel Rueckert, Julia A. Schnabel
Mask, Stitch, and Re-Sample: Enhancing Robustness and Generalizability in Anomaly Detection through Automatic Diffusion Models. CoRR (2023)
Sophia J. Wagner, Daniel Reisenbüchler, Nicholas P. West, Jan Moritz Niehues, Gregory Patrick Veldhuizen, Philip Quirke, Heike Irmgard Grabsch, Piet A. van den Brandt, Gordon G. A. Hutchins, Susan D. Richman, Tanwei Yuan, Rupert Langer, Josien Christina Anna Jenniskens, Kelly Offermans, Wolfram Müller, Richard Gray, Stephen B. Gruber, Joel K. Greenson, Gad Rennert, Joseph D. Bonner, Daniel Schmolze, Jacqueline A. James, Maurice B. Loughrey, Manuel Salto-Tellez, Hermann Brenner, Michael Hoffmeister, Daniel Truhn, Julia A. Schnabel, Melanie Boxberg, Tingying Peng, Jakob Nikolas Kather
Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study. CoRR (2023)
Josh Stein, Maxime Di Folco, Julia A. Schnabel
Sparse Annotation Strategies for Segmentation of Short Axis Cardiac MRI. STACOM@MICCAI (2023)
Josh Stein, Maxime Di Folco, Julia A. Schnabel
Sparse annotation strategies for segmentation of short axis cardiac MRI. CoRR (2023)
Maxime Di Folco, Cosmin Bercea, Julia A. Schnabel
Attribute Regularized Soft Introspective VAE: Towards Cardiac Attribute Regularization Through MRI Domains. CoRR (2023)
Alejandra Castelblanco, Giusy Matzeu, Elisabetta Ruggeri, Fiorenzo G. Omenetto, Anne Hilgendorff, Julia A. Schnabel, Benjamin Schubert
Colorimetric Sensor Reading and Illumination Correction via Multi-Task Deep-Learning. EMBC (2023)
Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F. Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R. Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard Ohene Botwe, Bishesh Khanal, Brigit Beger, Carol C. Wu, Celia Cintas, Curtis P. Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I. Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A. González, Folkert W. Asselbergs, Fred W. Prior, Gabriel P. Krestin, Gary S. Collins, Geletaw Sahle Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C. Woodruff, Hugo J. W. L. Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Islem Rekik, James S. Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W. Gichoya, Julia A. Schnabel, et al.
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare. CoRR (2023)
Martin J. Menten, Johannes C. Paetzold, Veronika A. Zimmer, Suprosanna Shit, Ivan Ezhov, Robbie Holland, Monika Probst, Julia A. Schnabel, Daniel Rueckert
A skeletonization algorithm for gradient-based optimization. CoRR (2023)
Cosmin I. Bercea, Esther Puyol-Antón, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel, Andrew P. King
Bias in Unsupervised Anomaly Detection in Brain MRI. CoRR (2023)
Cosmin I. Bercea, Daniel Rueckert, Julia A. Schnabel
What Do AEs Learn? Challenging Common Assumptions in Unsupervised Anomaly Detection. MICCAI (5) (2023)
Anna Reithmeir, Julia A. Schnabel, Veronika A. Zimmer
Learning Physics-Inspired Regularization for Medical Image Registration with Hypernetworks. CoRR (2023)
Veronika A. Zimmer, Kerstin Hammernik, Vasiliki Sideri-Lampretsa, Wenqi Huang, Anna Reithmeir, Daniel Rueckert, Julia A. Schnabel
Towards Generalised Neural Implicit Representations for Image Registration. DGM4MICCAI (2023)
Josh Stein, Maxime Di Folco, Julia A. Schnabel
Influence of Prompting Strategies on Segment Anything Model (SAM) for Short-axis Cardiac MRI segmentation. CoRR (2023)
Daniel Grzech, Mohammad Farid Azampour, Ben Glocker, Julia A. Schnabel, Nassir Navab, Bernhard Kainz, Loïc Le Folgoc
A variational Bayesian method for similarity learning in non-rigid image registration. CVPR (2022)
Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang
AtrialJSQnet: A New framework for joint segmentation and quantification of left atrium and scars incorporating spatial and shape information. Medical Image Anal. 76 (2022)
Emily Chan, Ciaran O'Hanlon, Carlota Asegurado Marquez, Marwenie Petalcorin, Jorge Mariscal Harana, Haotian Gu, Raymond J. Kim, Robert M. Judd, Philip J. Chowienczyk, Julia A. Schnabel, Reza Razavi, Andrew P. King, Bram Ruijsink, Esther Puyol-Antón
Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging. STACOM@MICCAI (2022)
Veronika A. Zimmer, Alberto Gómez, Emily Skelton, Robert Wright, Gavin Wheeler, Shujie Deng, Nooshin Ghavami, Karen Lloyd, Jacqueline Matthew, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel
Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View. CoRR (2022)
Cosmin I. Bercea, Daniel Rueckert, Julia A. Schnabel
What do we learn? Debunking the Myth of Unsupervised Outlier Detection. CoRR (2022)
Alberto Gómez, Veronika A. Zimmer, Gavin Wheeler, Nicolas Toussaint, Shujie Deng, Robert Wright, Emily Skelton, Jackie Matthews, Bernhard Kainz, Joseph V. Hajnal, Julia A. Schnabel
PRETUS: A plug-in based platform for real-time ultrasound imaging research. SoftwareX 17 (2022)
James R. Clough, Nicholas Byrne, Ilkay Öksüz, Veronika A. Zimmer, Julia A. Schnabel, Andrew P. King
A Topological Loss Function for Deep-Learning Based Image Segmentation Using Persistent Homology. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Emily Chan, Ciaran O'Hanlon, Carlota Asegurado Marquez, Marwenie Petalcorin, Jorge Mariscal Harana, Haotian Gu, Raymond J. Kim, Robert M. Judd, Philip J. Chowienczyk, Julia A. Schnabel, Reza Razavi, Andrew P. King, Bram Ruijsink, Esther Puyol-Antón
Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging. CoRR (2022)
Natasha Stephenson, Kuberan Pushparajah, Gavin Wheeler, Shujie Deng, Julia A. Schnabel, John M. Simpson
Evaluation of a Linear Measurement Tool in Virtual Reality for Assessment of Multimodality Imaging Data - A Phantom Study. J. Imaging 8 (11) (2022)
Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang
Medical image analysis on left atrial LGE MRI for atrial fibrillation studies: A review. Medical Image Anal. 77 (2022)
Inês Prata Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Ihsane Olakorede, Ilkay Öksüz, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King
A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis. CoRR (2022)
Vasileios Baltatzis, Loïc Le Folgoc, Sam Ellis, Octavio E. Martinez Manzanera, Kyriaki-Margarita Bintsi, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data. iMIMIC/TDA4MedicalData@MICCAI (2021)
Shujie Deng, Gavin Wheeler, Nicolas Toussaint, Lindsay Munroe, Suryava Bhattacharya, Gina Sajith, Ei Lin, Eeshar Singh, Ka Yee Kelly Chu, Saleha Kabir, Kuberan Pushparajah, John M. Simpson, Julia A. Schnabel, Alberto Gómez
A Virtual Reality System for Improved Image-Based Planning of Complex Cardiac Procedures. J. Imaging 7 (8) (2021)
Alberto Gómez, Veronika A. Zimmer, Gavin Wheeler, Nicolas Toussaint, Shujie Deng, Robert Wright, Emily Skelton, Jackie Matthews, Bernhard Kainz, Joseph V. Hajnal, Julia A. Schnabel
PRETUS: A plug-in based platform for real-time ultrasound imaging research. CoRR (2021)
Loïc Le Folgoc, Vasileios Baltatzis, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Arjun Nair, Huaqi Qiu, Julia A. Schnabel, Ben Glocker
Is MC Dropout Bayesian? CoRR (2021)
Inês Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King
Quality-Aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled K-Space Data. STACOM@MICCAI (2021)
Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang
Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review. CoRR (2021)
Octavio E. Martinez Manzanera, Sam Ellis, Vasileios Baltatzis, Arjun Nair, Loïc Le Folgoc, Sujal Desai, Ben Glocker, Julia A. Schnabel
Patient-Specific 3d Cellular Automata Nodule Growth Synthesis In Lung Cancer Without The Need Of External Data. ISBI (2021)
Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loïc Le Folgoc, Octavio E. Martinez Manzanera, Sam Ellis, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification. CoRR (2021)
Emily Chan, Matt Kelly, Julia A. Schnabel
Comparison of Classical Machine Learning & Deep Learning to Characterise Fibrosis & Inflammation Using Quantitative MRI. ISBI (2021)
Devran Ugurlu, Esther Puyol-Antón, Bram Ruijsink, Alistair A. Young, Inês Machado, Kerstin Hammernik, Andrew P. King, Julia A. Schnabel
The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images. CoRR (2021)
Devran Ugurlu, Esther Puyol-Antón, Bram Ruijsink, Alistair A. Young, Inês Machado, Kerstin Hammernik, Andrew P. King, Julia A. Schnabel
The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images. STACOM@MICCAI (2021)
Vasileios Baltatzis, Loïc Le Folgoc, Sam Ellis, Octavio E. Martinez Manzanera, Kyriaki-Margarita Bintsi, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data. CoRR (2021)
Lindsay Munroe, Gina Sajith, Ei Lin, Surjava Bhattacharya, Kuberan Pushparajah, John M. Simpson, Julia A. Schnabel, Gavin Wheeler, Alberto Gómez, Shujie Deng
Automatic Re-orientation of 3D Echocardiographic Images in Virtual Reality Using Deep Learning. MIUA (2021)
Loïc Le Folgoc, Vasileios Baltatzis, Amir Alansary, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Fahdi Kanavati, Arjun Nair, Julia A. Schnabel, Ben Glocker
Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data. CoRR (2021)
Inês Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King
Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data. CoRR (2021)
Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang
AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-Center LGE MRIs. CoRR (2021)
Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang
AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-center LGE MRIs. MICCAI (6) (2021)
Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loïc Le Folgoc, Octavio E. Martinez Manzanera, Sam Ellis, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification. PRIME@MICCAI (2021)
Veronika A. Zimmer, Alberto Gómez, Emily Skelton, Nooshin Ghavami, Robert Wright, Lei Li, Jacqueline Matthew, Joseph V. Hajnal, Julia A. Schnabel
A Multi-task Approach Using Positional Information for Ultrasound Placenta Segmentation. ASMUS/PIPPI@MICCAI (2020)
Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang
AtrialJSQnet: A New Framework for Joint Segmentation and Quantification of Left Atrium and Scars Incorporating Spatial and Shape Information. CoRR (2020)
Yiming Xiao, Andreas Maier, Wolfgang Wein, Roozbeh Shams, Samuel Kadoury, David Drobny, Marc Modat, Ingerid Reinertsen, Hassan Rivaz, Matthieu Chabanas, Maryse Fortin, Inês Machado, Yangming Ou, Mattias P. Heinrich, Julia A. Schnabel, Xia Zhong
Evaluation of MRI to Ultrasound Registration Methods for Brain Shift Correction: The CuRIOUS2018 Challenge. IEEE Trans. Medical Imaging 39 (3) (2020)
Lei Li, Xin Weng, Julia A. Schnabel, Xiahai Zhuang
Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention. MICCAI (4) (2020)
Lei Li, Veronika A. Zimmer, Wangbin Ding, Fuping Wu, Liqin Huang, Julia A. Schnabel, Xiahai Zhuang
Random Style Transfer Based Domain Generalization Networks Integrating Shape and Spatial Information. M&Ms and EMIDEC/STACOM@MICCAI (2020)
Lei Li, Xin Weng, Julia A. Schnabel, Xiahai Zhuang
Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention. CoRR (2020)
Daniel Rueckert, Julia A. Schnabel
Model-Based and Data-Driven Strategies in Medical Image Computing. Proc. IEEE 108 (1) (2020)
Bartlomiej W. Papiez, Bostjan Markelc, Graham Brown, Ruth J. Muschel, Michael Brady, Julia A. Schnabel
Image-Based Artefact Removal in Laser Scanning Microscopy. IEEE Trans. Biomed. Eng. 67 (1) (2020)
Lei Li, Veronika A. Zimmer, Wangbin Ding, Fuping Wu, Liqin Huang, Julia A. Schnabel, Xiahai Zhuang
Random Style Transfer based Domain Generalization Networks Integrating Shape and Spatial Information. CoRR (2020)
Ilkay Öksüz, James R. Clough, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Andrew P. King, Julia A. Schnabel
Deep Learning-Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation. IEEE Trans. Medical Imaging 39 (12) (2020)
Cesare Magnetti, Veronika A. M. Zimmer, Nooshin Ghavami, Emily Skelton, Jacqueline Matthew, Karen Lloyd, Joseph V. Hajnal, Julia A. Schnabel, Alberto Gómez
Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time. MIUA (2020)
Caifeng Shan, Tao Tan, Shandong Wu, Julia A. Schnabel
Guest Editorial: Deep Learning in Ultrasound Imaging. IEEE J. Biomed. Health Informatics 24 (4) (2020)
Simona Treivase, Alberto Gómez, Jacqueline Matthew, Emily Skelton, Julia A. Schnabel, Nicolas Toussaint
Screen Tracking for Clinical Translation of Live Ultrasound Image Analysis Methods. CoRR (2020)
Loïc Le Folgoc, Vasileios Baltatzis, Amir Alansary, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Fahdi Kanavati, Arjun Nair, Julia A. Schnabel, Ben Glocker
Bayesian Sampling Bias Correction: Training with the Right Loss Function. CoRR (2020)
Ilkay Öksüz, Gastão Cruz, James R. Clough, Aurélien Bustin, Nicolo Fuin, René M. Botnar, Claudia Prieto, Andrew P. King, Julia A. Schnabel
Magnetic Resonance Fingerprinting Using Recurrent Neural Networks. ISBI (2019)
Robert Wright, Nicolas Toussaint, Alberto Gómez, Veronika A. M. Zimmer, Bishesh Khanal, Jacqueline Matthew, Emily Skelton, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel
Complete Fetal Head Compounding from Multi-view 3D Ultrasound. MICCAI (3) (2019)
Ilkay Öksüz, James R. Clough, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Andrew P. King, Julia A. Schnabel
Detection and Correction of Cardiac MR Motion Artefacts during Reconstruction from K-space. CoRR (2019)
Qingjie Meng, James Housden, Jacqueline Matthew, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz, Matthew Sinclair, Veronika A. Zimmer, Benjamin Hou, Martin Rajchl, Nicolas Toussaint, Ozan Oktay, Jo Schlemper, Alberto Gómez
Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging. IEEE Trans. Medical Imaging 38 (12) (2019)
James R. Clough, Ilkay Öksüz, Esther Puyol-Antón, Bram Ruijsink, Andrew P. King, Julia A. Schnabel
Global and Local Interpretability for Cardiac MRI Classification. CoRR (2019)

Julia A. Schnabel.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Julia A. Schnabel