Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Julia A. Schnabel

Julia A. Schnabel
Alert button

Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review


May 11, 2023
Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik, Daniel Rueckert, Christine Preibisch, Dimitrios C. Karampinos, Julia A. Schnabel

Add code
Alert button

Figure 1 for Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review
Figure 2 for Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review
Figure 3 for Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Deep Learning-Based Detection of Motion-Affected k-Space Lines for T2*-Weighted MRI


Mar 20, 2023
Hannah Eichhorn, Kerstin Hammernik, Veronika Spieker, Samira M. Epp, Daniel Rueckert, Christine Preibisch, Julia A. Schnabel

Add code
Alert button

Figure 1 for Deep Learning-Based Detection of Motion-Affected k-Space Lines for T2*-Weighted MRI
Figure 2 for Deep Learning-Based Detection of Motion-Affected k-Space Lines for T2*-Weighted MRI
Figure 3 for Deep Learning-Based Detection of Motion-Affected k-Space Lines for T2*-Weighted MRI
* Submitted to MICCAI 2023 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

3D Masked Autoencoders with Application to Anomaly Detection in Non-Contrast Enhanced Breast MRI


Mar 10, 2023
Daniel M. Lang, Eli Schwartz, Cosmin I. Bercea, Raja Giryes, Julia A. Schnabel

Add code
Alert button

Figure 1 for 3D Masked Autoencoders with Application to Anomaly Detection in Non-Contrast Enhanced Breast MRI
Figure 2 for 3D Masked Autoencoders with Application to Anomaly Detection in Non-Contrast Enhanced Breast MRI
Figure 3 for 3D Masked Autoencoders with Application to Anomaly Detection in Non-Contrast Enhanced Breast MRI
Figure 4 for 3D Masked Autoencoders with Application to Anomaly Detection in Non-Contrast Enhanced Breast MRI

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study


Jan 23, 2023
Sophia J. Wagner, Daniel Reisenbüchler, Nicholas P. West, Jan Moritz Niehues, Gregory Patrick Veldhuizen, Philip Quirke, Heike I. Grabsch, Piet A. van den Brandt, Gordon G. A. Hutchins, Susan D. Richman, Tanwei Yuan, Rupert Langer, Josien Christina Anna Jenniskens, Kelly Offermans, Wolfram Mueller, 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

Add code
Alert button

Figure 1 for Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study
Figure 2 for Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study
Figure 3 for Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study
Figure 4 for Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging


Sep 28, 2022
Emily Chan, Ciaran O'Hanlon, Carlota Asegurado Marquez, Marwenie Petalcorin, Jorge Mariscal-Harana, Haotian Gu, Raymond J. Kim, Robert M. Judd, Phil Chowienczyk, Julia A. Schnabel, Reza Razavi, Andrew P. King, Bram Ruijsink, Esther Puyol-Antón

Add code
Alert button

Figure 1 for Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging
Figure 2 for Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging
Figure 3 for Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging
Figure 4 for Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging
* STACOM 2022 workshop 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Evaluation of 3D GANs for Lung Tissue Modelling in Pulmonary CT


Aug 17, 2022
Sam Ellis, Octavio E. Martinez Manzanera, Vasileios Baltatzis, Ibrahim Nawaz, Arjun Nair, Loïc Le Folgoc, Sujal Desai, Ben Glocker, Julia A. Schnabel

Add code
Alert button

Figure 1 for Evaluation of 3D GANs for Lung Tissue Modelling in Pulmonary CT
Figure 2 for Evaluation of 3D GANs for Lung Tissue Modelling in Pulmonary CT
Figure 3 for Evaluation of 3D GANs for Lung Tissue Modelling in Pulmonary CT
Figure 4 for Evaluation of 3D GANs for Lung Tissue Modelling in Pulmonary CT
* Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://www.melba-journal.org/papers/2022:024.html 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View


Jun 29, 2022
Veronika A. Zimmer, Alberto Gomez, Emily Skelton, Robert Wright, Gavin Wheeler, Shujie Deng, Nooshin Ghavami, Karen Lloyd, Jacqueline Matthew, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel

Add code
Alert button

Figure 1 for Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View
Figure 2 for Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View
Figure 3 for Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View
Figure 4 for Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View
* 21 pages (18 + appendix), 13 figures (9 + appendix) 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

What do we learn? Debunking the Myth of Unsupervised Outlier Detection


Jun 08, 2022
Cosmin I. Bercea, Daniel Rueckert, Julia A. Schnabel

Add code
Alert button

Figure 1 for What do we learn? Debunking the Myth of Unsupervised Outlier Detection
Figure 2 for What do we learn? Debunking the Myth of Unsupervised Outlier Detection
Figure 3 for What do we learn? Debunking the Myth of Unsupervised Outlier Detection
Figure 4 for What do we learn? Debunking the Myth of Unsupervised Outlier Detection

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis


May 02, 2022
Inês P. Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Ihsane Olakorede, Ilkay Oksuz, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King

Add code
Alert button

Figure 1 for A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis
Figure 2 for A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis
Figure 3 for A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis
Figure 4 for A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images


Sep 22, 2021
Devran Ugurlu, Esther Puyol-Anton, Bram Ruijsink, Alistair Young, Ines Machado, Kerstin Hammernik, Andrew P. King, Julia A. Schnabel

Add code
Alert button

Figure 1 for The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images
Figure 2 for The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images
Figure 3 for The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images
Figure 4 for The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images
* Accepted to STACOM 2021 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
1
2
3
4
5
>>