Deep Learning for Magnetic Resonance Imaging (MRI)


Magnetic Resonance Imaging (MRI) can be used in many types of diagnosis e.g. cancer, alzheimer, cardiac and muscle/skeleton issues. This blog post has recent publications of Deep Learning applied to MRI (health-related) data, e.g. for segmentation, detection, demonising and classification.

MRI is described in Wikipedia as:

    Magnetic resonance imaging (MRI) is a medical imaging technique used in radiology to form pictures of the anatomy and the physiological processes of the body in both health and disease. MRI scanners use strong magnetic fields, radio waves, and field gradients to generate images of the organs in the body.

Best regards,
Amund Tveit

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

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