3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study (2016-12-12T00:00:00.000000Z)

TL;DR

This work is the first to study subcortical structure segmentation on such large‐scale and heterogeneous data and yielded segmentations that are highly consistent with a standard atlas‐based approach, while running in a fraction of the time needed by atlas-based methods and avoiding registration/normalization steps.

Authors

Christian Desrosiers

6 papers

Ismail Ben Ayed

11 papers

J. Dolz

14 papers

TL;DR

Authors

References73 items

Multi-scale structured CNN with label consistency for brain MR image segmentation

Consistent cortical reconstruction and multi-atlas brain segmentation

Automatic Segmentation of MR Brain Images With a Convolutional Neural Network

Efficient multi‐scale 3D CNN with fully connected CRF for accurate brain lesion segmentation

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

Sub-cortical brain structure segmentation using F-CNN'S

Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound

Multi-Scale Context Aggregation by Dilated Convolutions

Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform

Autism spectrum disorders and neuropathology of the cerebellum

Deep Convolutional Encoder Networks for Multiple Sclerosis Lesion Segmentation

Segmentation algorithms of subcortical brain structures on MRI for radiotherapy and radiosurgery: A survey

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium

Brain tumor segmentation with Deep Neural Networks

Subcortical Structure Volumes and Correlation to Clinical Variables in Parkinson's Disease

Deep convolutional neural networks for multi-modality isointense infant brain image segmentation

Deep neural networks for anatomical brain segmentation

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Increased Putamen Volume in Adults with Autism Spectrum Disorder

Hypercolumns for object segmentation and fine-grained localization

Fully convolutional networks for semantic segmentation

Going deeper with convolutions

Very Deep Convolutional Networks for Large-Scale Image Recognition

Groupwise multi-atlas segmentation of the spinal cord's internal structure

Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline

Learning Hierarchical Features for Scene Labeling

The Autism Brain Imaging Data Exchange: Towards Large-Scale Evaluation of the Intrinsic Brain Architecture in Autism

Multi-Atlas Segmentation with Joint Label Fusion

Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images

ImageNet classification with deep convolutional neural networks

FreeSurfer

Segmentation of multiple sclerosis lesions in brain MRI: A review of automated approaches

Comparison of manual and automatic segmentation methods for brain structures in the presence of space-occupying lesions: a multi-expert study

Towards a deep learning approach to brain parcellation

A Bayesian model of shape and appearance for subcortical brain segmentation

A Supervised Patch-Based Approach for Human Brain Labeling

Optimal weights for local multi-atlas fusion using supervised learning and dynamic information (SuperDyn): Validation on hippocampus segmentation

Evaluating the validity of volume-based and surface-based brain image registration for developmental cognitive neuroscience studies in children 4 to 11years of age

Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition

A Generative Model for Image Segmentation Based on Label Fusion

Fast and robust multi-atlas segmentation of brain magnetic resonance images

Changes in the Developmental Trajectories of Striatum in Autism

Brain volume abnormalities in major depressive disorder: a Meta-analysis of magnetic resonance imaging studies

Atlas-based segmentation of 3D cerebral structures with competitive level sets and fuzzy control

Combination Strategies in Multi-Atlas Image Segmentation: Application to Brain MR Data

Homeomorphic brain image segmentation with topological and statistical atlases

3D Brain Segmentation Using Active Appearance Models and Local Regressors

FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping

Hierarchical statistical shape analysis and prediction of sub-cortical brain structures

Registration and machine learning-based automated segmentation of subcortical and cerebellar brain structures

Atlas Renormalization for Improved Brain MR Image Segmentation Across Scanner Platforms

Detection and mapping of hippocampal abnormalities in autism

Automatic anatomical brain MRI segmentation combining label propagation and decision fusion

Hierarchical Statistical Shape Analysis and Prediction of Sub-Cortical Brain Structures

3D image segmentation of deformable objects with joint shape-intensity prior models using level sets

The Amygdala Is Enlarged in Children But Not Adolescents with Autism; the Hippocampus Is Enlarged at All Ages

High Accuracy Optical Flow Estimation Based on a Theory for Warping

The Medical Imaging Interaction Toolkit

Fast robust automated brain extraction

Effects of age on brain volume and head circumference in autism

Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data

Proceedings of the Eighteenth International Conference on Machine Learning

Corpus callosum size in autism

Measures of the Amount of Ecologic Association Between Species

Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context

Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging

Motor stereotypies and volumetric brain alterations in children with Autistic Disorder.

Yushke- vich, Multi-atlas segmentation with joint label fusion, IEEE transactions on pattern analysis and machine intelligence

Neuroimage

Theano: A CPU and GPU Math Compiler in Python

Segmentation propagation from deformable atlases for brain mapping and analysis

Gradient-based learning applied to document recognition

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