Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science

ISLES (SISS) Challenge 2015: Segmentation of Stroke Lesions Using Spatial Normalization, Random Forest Classification and Contextual Clustering

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science ◽

10.1007/978-3-319-30858-6_18 ◽

2016 ◽

pp. 211-221 ◽

Cited By ~ 3

Author(s):

Hanna-Leena Halme ◽

Antti Korvenoja ◽

Eero Salli

Keyword(s):

Random Forest ◽

Spatial Normalization ◽

Random Forest Classification ◽

Forest Classification

Download Full-text

Parameter Learning for CRF-Based Tissue Segmentation of Brain Tumors

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science ◽

10.1007/978-3-319-30858-6_14 ◽

2016 ◽

pp. 156-167 ◽

Cited By ~ 3

Author(s):

Raphael Meier ◽

Venetia Karamitsou ◽

Simon Habegger ◽

Roland Wiest ◽

Mauricio Reyes

Keyword(s):

Brain Tumors ◽

Parameter Learning ◽

Tissue Segmentation

Download Full-text

ISLES Challenge 2015: Automated Model-Based Segmentation of Ischemic Stroke in MR Images

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science ◽

10.1007/978-3-319-30858-6_21 ◽

2016 ◽

pp. 246-253 ◽

Cited By ~ 2

Author(s):

Tom Haeck ◽

Frederik Maes ◽

Paul Suetens

Keyword(s):

Ischemic Stroke ◽

Mr Images ◽

Model Based

Download Full-text

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science ◽

10.1007/978-3-319-30858-6_13 ◽

2016 ◽

pp. 144-155 ◽

Cited By ~ 14

Author(s):

Spyridon Bakas ◽

Ke Zeng ◽

Aristeidis Sotiras ◽

Saima Rathore ◽

Hamed Akbari ◽

...

Keyword(s):

Tumor Growth ◽

Growth Modeling ◽

Gradient Boosting ◽

Mri Segmentation ◽

Multimodal Mri ◽

Tumor Growth Modeling

Download Full-text

Image Features for Brain Lesion Segmentation Using Random Forests

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science ◽

10.1007/978-3-319-30858-6_11 ◽

2016 ◽

pp. 119-130 ◽

Cited By ~ 5

Author(s):

Oskar Maier ◽

Matthias Wilms ◽

Heinz Handels

Keyword(s):

Random Forests ◽

Brain Lesion ◽

Image Features ◽

Lesion Segmentation

Download Full-text

Combining Unsupervised and Supervised Methods for Lesion Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science ◽

10.1007/978-3-319-30858-6_5 ◽

2016 ◽

pp. 45-56 ◽

Cited By ~ 3

Author(s):

Tim Jerman ◽

Alfiia Galimzianova ◽

Franjo Pernuš ◽

Boštjan Likar ◽

Žiga Špiclin

Keyword(s):

Lesion Segmentation ◽

Supervised Methods

Download Full-text

A Voxel-Wise, Cascaded Classification Approach to Ischemic Stroke Lesion Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science ◽

10.1007/978-3-319-30858-6_22 ◽

2016 ◽

pp. 254-265 ◽

Cited By ~ 2

Author(s):

David Robben ◽

Daan Christiaens ◽

Janaki Raman Rangarajan ◽

Jaap Gelderblom ◽

Philip Joris ◽

...

Keyword(s):

Ischemic Stroke ◽

Lesion Segmentation ◽

Classification Approach ◽

Stroke Lesion

Download Full-text

A Semi-automatic Method for Segmentation of Multiple Sclerosis Lesions on Dual-Echo Magnetic Resonance Images

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science ◽

10.1007/978-3-319-30858-6_8 ◽

2016 ◽

pp. 80-90 ◽

Cited By ~ 1

Author(s):

Loredana Storelli ◽

Elisabetta Pagani ◽

Maria Assunta Rocca ◽

Mark A. Horsfield ◽

Massimo Filippi

Keyword(s):

Multiple Sclerosis ◽

Magnetic Resonance ◽

Magnetic Resonance Images ◽

Automatic Method ◽

Dual Echo

Download Full-text

Multi-modal Brain Tumor Segmentation Using Stacked Denoising Autoencoders

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science ◽

10.1007/978-3-319-30858-6_16 ◽

2016 ◽

pp. 181-194 ◽

Cited By ~ 6

Author(s):

Kiran Vaidhya ◽

Subramaniam Thirunavukkarasu ◽

Varghese Alex ◽

Ganapathy Krishnamurthi

Keyword(s):

Brain Tumor ◽

Tumor Segmentation ◽

Brain Tumor Segmentation

Download Full-text

Deep Convolutional Neural Networks for the Segmentation of Gliomas in Multi-sequence MRI

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science ◽

10.1007/978-3-319-30858-6_12 ◽

2016 ◽

pp. 131-143 ◽

Cited By ~ 28

Author(s):

Sérgio Pereira ◽

Adriano Pinto ◽

Victor Alves ◽

Carlos A. Silva

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Deep Convolutional Neural Networks

Download Full-text

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science
Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

ISLES (SISS) Challenge 2015: Segmentation of Stroke Lesions Using Spatial Normalization, Random Forest Classification and Contextual Clustering

Parameter Learning for CRF-Based Tissue Segmentation of Brain Tumors

ISLES Challenge 2015: Automated Model-Based Segmentation of Ischemic Stroke in MR Images

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation

Image Features for Brain Lesion Segmentation Using Random Forests

Combining Unsupervised and Supervised Methods for Lesion Segmentation

A Voxel-Wise, Cascaded Classification Approach to Ischemic Stroke Lesion Segmentation

A Semi-automatic Method for Segmentation of Multiple Sclerosis Lesions on Dual-Echo Magnetic Resonance Images

Multi-modal Brain Tumor Segmentation Using Stacked Denoising Autoencoders

Deep Convolutional Neural Networks for the Segmentation of Gliomas in Multi-sequence MRI

Export Citation Format

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

ISLES (SISS) Challenge 2015: Segmentation of Stroke Lesions Using Spatial Normalization, Random Forest Classification and Contextual Clustering

Parameter Learning for CRF-Based Tissue Segmentation of Brain Tumors

ISLES Challenge 2015: Automated Model-Based Segmentation of Ischemic Stroke in MR Images

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation

Image Features for Brain Lesion Segmentation Using Random Forests

Combining Unsupervised and Supervised Methods for Lesion Segmentation

A Voxel-Wise, Cascaded Classification Approach to Ischemic Stroke Lesion Segmentation

A Semi-automatic Method for Segmentation of Multiple Sclerosis Lesions on Dual-Echo Magnetic Resonance Images

Multi-modal Brain Tumor Segmentation Using Stacked Denoising Autoencoders

Deep Convolutional Neural Networks for the Segmentation of Gliomas in Multi-sequence MRI

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - Lecture Notes in Computer Science
Latest Publications