Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions
Authors
Keywords
Deep learning, Quantitative brain MRI, Convolutional neural network, Brain lesion segmentation
Journal
JOURNAL OF DIGITAL IMAGING
Volume 30, Issue 4, Pages 449-459
Publisher
Springer Nature
Online
2017-06-03
DOI
10.1007/s10278-017-9983-4
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Large scale deep learning for computer aided detection of mammographic lesions
- (2017) Thijs Kooi et al. MEDICAL IMAGE ANALYSIS
- Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
- (2017) Konstantinos Kamnitsas et al. MEDICAL IMAGE ANALYSIS
- Brain tumor segmentation with Deep Neural Networks
- (2017) Mohammad Havaei et al. MEDICAL IMAGE ANALYSIS
- Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation
- (2016) Tom Brosch et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Automatic Segmentation of MR Brain Images With a Convolutional Neural Network
- (2016) Pim Moeskops et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks
- (2016) Qi Dou et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
- (2016) Hoo-Chang Shin et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Neural networks for computer-aided diagnosis in medicine: A review
- (2016) Di lin et al. NEUROCOMPUTING
- Stratified mixture modeling for segmentation of white-matter lesions in brain MR images
- (2016) Alfiia Galimzianova et al. NEUROIMAGE
- Deep MRI brain extraction: A 3D convolutional neural network for skull stripping
- (2016) Jens Kleesiek et al. NEUROIMAGE
- Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans
- (2016) Jie-Zhi Cheng et al. Scientific Reports
- Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis
- (2016) Geert Litjens et al. Scientific Reports
- Bayesian Model Selection for Pathological Neuroimaging Data Applied to White Matter Lesion Segmentation
- (2015) Carole H. Sudre et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Temporal Hierarchical Adaptive Texture CRF for Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI
- (2015) Zahra Karimaghaloo et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- A Model of Population and Subject (MOPS) Intensities With Application to Multiple Sclerosis Lesion Segmentation
- (2015) Xavier Tomas-Fernandez et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
- (2015) Bjoern H. Menze et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- ImageNet Large Scale Visual Recognition Challenge
- (2015) Olga Russakovsky et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Deep learning
- (2015) Yann LeCun et al. NATURE
- LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images
- (2015) Li Wang et al. NEUROIMAGE
- Deep convolutional neural networks for multi-modality isointense infant brain image segmentation
- (2015) Wenlu Zhang et al. NEUROIMAGE
- Automatic segmentation of MR brain images of preterm infants using supervised classification
- (2015) Pim Moeskops et al. NEUROIMAGE
- Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study
- (2015) Oskar Maier et al. PLoS One
- A Logarithmic Opinion Pool Based STAPLE Algorithm for the Fusion of Segmentations With Associated Reliability Weights
- (2014) Alireza Akhondi-Asl et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain
- (2014) Antonios Makropoulos et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- A survey of MRI-based medical image analysis for brain tumor studies
- (2013) Stefan Bauer et al. PHYSICS IN MEDICINE AND BIOLOGY
- Automatic Segmentation of Eight Tissue Classes in Neonatal Brain MRI
- (2013) Petronella Anbeek et al. PLoS One
- Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging
- (2012) Daniel García-Lorenzo et al. MEDICAL IMAGE ANALYSIS
- Robust Brain Extraction Across Datasets and Comparison With Publicly Available Methods
- (2011) J. E. Iglesias et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Automated detection of multiple sclerosis lesions in serial brain MRI
- (2011) Xavier Lladó et al. NEURORADIOLOGY
- Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration
- (2009) Arno Klein et al. NEUROIMAGE
- A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions
- (2009) Navid Shiee et al. NEUROIMAGE
- An Optimized Blockwise Nonlocal Means Denoising Filter for 3-D Magnetic Resonance Images
- (2008) P. Coupe et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Construction of a 3D probabilistic atlas of human cortical structures
- (2007) David W. Shattuck et al. NEUROIMAGE
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now