Year |
Title |
Author |

2017 |
Residual and Plain Convolutional Neural Networks for 3D Brain MRI Classification |
S Korolev, A Safiullin, M Belyaev, Y Dodonova |

2017 |
Automatic segmentation of the right ventricle from cardiac MRI using a learning‐based approach |
MR Avendi, A Kheradvar, H Jafarkhani |

2017 |
Learning a Variational Network for Reconstruction of Accelerated MRI Data |
K Hammernik, T Klatzer, E Kobler, MP Recht |

2017 |
A 2D/3D Convolutional Neural Network for Brain White Matter Lesion Detection in Multimodal MRI |
L Roa |

2017 |
On hierarchical brain tumor segmentation in MRI using fully convolutional neural networks: A preliminary study |
S Pereira, A Oliveira, V Alves, CA Silva |

2017 |
Classification of breast MRI lesions using small-size training sets: comparison of deep learning approaches |
G Amit, R Ben |

2017 |
A deep learning network for right ventricle segmentation in short-axis MRI |
GN Luo, R An, KQ Wang, SY Dong, HG Zhang |

2017 |
A novel left ventricular volumes prediction method based on deep learning network in cardiac MRI |
GN Luo, GX Sun, KQ Wang, SY Dong, HG Zhang |

2017 |
Classification of MRI data using Deep Learning and Gaussian Process-based Model Selection |
H Bertrand, M Perrot, R Ardon, I Bloch |

2017 |
Using Deep Learning to Segment Breast and Fibroglanduar Tissue in MRI Volumes |
MU Dalmş, G Litjens, K Holland, A Setio, R Mann |

2017 |
Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks |
PF Christ, F Ettlinger, F Grün, MEA Elshaera, J Lipkova |

2017 |
Automated Segmentation of Hyperintense Regions in FLAIR MRI Using Deep Learning |
P Korfiatis, TL Kline, BJ Erickson |

2017 |
Automatic segmentation of left ventricle in cardiac cine MRI images based on deep learning |
T Zhou, I Icke, B Dogdas, S Parimal, S Sampath |

2017 |
Deep artifact learning for compressed sensing and parallel MRI |
D Lee, J Yoo, JC Ye |

2017 |
Deep Generative Adversarial Networks for Compressed Sensing Automates MRI |
M Mardani, E Gong, JY Cheng, S Vasanawala |

2017 |
3D Motion Modeling and Reconstruction of Left Ventricle Wall in Cardiac MRI |
D Yang, P Wu, C Tan, KM Pohl, L Axel, D Metaxas |

2017 |
Estimation of the volume of the left ventricle from MRI images using deep neural networks |
F Liao, X Chen, X Hu, S Song |

2017 |
A fully automatic deep learning method for atrial scarring segmentation from late gadolinium-enhanced MRI images |
G Yang, X Zhuang, H Khan, S Haldar, E Nyktari, X Ye |

2017 |
Age estimation from brain MRI images using deep learning |
TW Huang, HT Chen, R Fujimoto, K Ito, K Wu, K Sato |

2017 |
Segmenting Atrial Fibrosis from Late Gadolinium-Enhanced Cardiac MRI by Deep-Learned Features with Stacked Sparse Auto-Encoders |
S Haldar, E Nyktari, X Ye, G Slabaugh, T Wong |

2017 |
Deep Residual Learning For Compressed Sensing Mri |
D Lee, J Yoo, JC Ye |

2017 |
Prostate cancer diagnosis using deep learning with 3D multiparametric MRI |
S Liu, H Zheng, Y Feng, W Li |

2017 |
Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions |
Z Akkus, A Galimzianova, A Hoogi, DL Rubin |

2016 |
Classification of Alzheimer’s Disease Structural MRI Data by Deep Learning Convolutional Neural Networks |
S Sarraf, G Tofighi |

2016 |
De-noising of Contrast-Enhanced MRI Sequences by an Ensemble of Expert Deep Neural Networks |
A Benou, R Veksler, A Friedman, TR Raviv |

2016 |
A Combined Deep-Learning and Deformable-Model Approach to Fully Automatic Segmentation of the Left Ventricle in Cardiac MRI |
MR Avendi, A Kheradvar, H Jafarkhani |

2016 |
Applying machine learning to automated segmentation of head and neck tumour volumes and organs at risk on radiotherapy planning CT and MRI scans |
C Chu, J De Fauw, N Tomasev, BR Paredes, C Hughes |

2016 |
A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI |
PV Tran |

2016 |
An Overview of Techniques for Cardiac Left Ventricle Segmentation on Short-Axis MRI |
A Krasnobaev, A Sozykin |

2016 |
Stacking denoising auto-encoders in a deep network to segment the brainstem on MRI in brain cancer patients: a clinical study |
J Dolz, N Betrouni, M Quidet, D Kharroubi, HA Leroy |

2016 |
Hough-CNN: Deep Learning for Segmentation of Deep Brain Regions in MRI and Ultrasound |
F Milletari, SA Ahmadi, C Kroll, A Plate, V Rozanski |

2016 |
Mental Disease Feature Extraction with MRI by 3D Convolutional Neural Network with Multi-channel Input |
L Cao, Z Liu, X He, Y Cao, K Li |

2016 |
Deep learning trends for focal brain pathology segmentation in MRI |
M Havaei, N Guizard, H Larochelle, PM Jodoin |

2016 |
Identification of Water and Fat Images in Dixon MRI Using Aggregated Patch-Based Convolutional Neural Networks |
L Zhao, Y Zhan, D Nickel, M Fenchel, B Kiefer, XS Zhou |

2016 |
Deep MRI brain extraction: A 3D convolutional neural network for skull stripping |
J Kleesiek, G Urban, A Hubert, D Schwarz |

2016 |
Active appearance model and deep learning for more accurate prostate segmentation on MRI |
R Cheng, HR Roth, L Lu, S Wang, B Turkbey |

2016 |
Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation |
RPK Poudel, P Lamata, G Montana |

2016 |
Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis |
HK van der Burgh, R Schmidt, HJ Westeneng |

2016 |
Semantic-Based Brain MRI Image Segmentation Using Convolutional Neural Network |
Y Chou, DJ Lee, D Zhang |

2016 |
Abstract WP41: Predicting Acute Ischemic Stroke Tissue Fate Using Deep Learning on Source Perfusion MRI |
KC Ho, S El |

2016 |
A new ASM framework for left ventricle segmentation exploring slice variability in cardiac MRI volumes |
C Santiago, JC Nascimento, JS Marques |

2015 |
Crohn’s disease segmentation from mri using learned image priors |
D Mahapatra, P Schüffler, F Vos, JM Buhmann |

2015 |
Discovery Radiomics for Multi-Parametric MRI Prostate Cancer Detection |
AG Chung, MJ Shafiee, D Kumar, F Khalvati |

2015 |
Real-time Dynamic MRI Reconstruction using Stacked Denoising Autoencoder |
A Majumdar |

2015 |
q-Space Deep Learning for Twelve-Fold Shorter and Model-Free Diffusion MRI Scans |
V Golkov, A Dosovitskiy, P Sämann, JI Sperl |