Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science

2020 ◽

pp. 98-107

Author(s):

Kyriaki-Margarita Bintsi ◽

Vasileios Baltatzis ◽

Arinbjörn Kolbeinsson ◽

Alexander Hammers ◽

Daniel Rueckert

Keyword(s):

Age Estimation ◽

Mr Images ◽

Brain Age

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Deep Voxel-Guided Morphometry (VGM): Learning Regional Brain Changes in Serial MRI

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science ◽

10.1007/978-3-030-66843-3_16 ◽

2020 ◽

pp. 159-168

Author(s):

Alena-Kathrin Schnurr ◽

Philipp Eisele ◽

Christina Rossmanith ◽

Stefan Hoffmann ◽

Johannes Gregori ◽

...

Keyword(s):

Regional Brain ◽

Brain Changes ◽

Serial Mri

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Towards MRI Progression Features for Glioblastoma Patients: From Automated Volumetry and Classical Radiomics to Deep Feature Learning

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science ◽

10.1007/978-3-030-66843-3_13 ◽

2020 ◽

pp. 129-138

Author(s):

Yannick Suter ◽

Urspeter Knecht ◽

Roland Wiest ◽

Ekkehard Hewer ◽

Philippe Schucht ◽

...

Keyword(s):

Feature Learning ◽

Deep Feature ◽

Deep Feature Learning

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Large-Scale Unbiased Neuroimage Indexing via 3D GPU-SIFT Filtering and Keypoint Masking

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science ◽

10.1007/978-3-030-66843-3_11 ◽

2020 ◽

pp. 108-118

Author(s):

Étienne Pepin ◽

Jean-Baptiste Carluer ◽

Laurent Chauvin ◽

Matthew Toews ◽

Rola Harmouche

Keyword(s):

Large Scale

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A Multi-task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science ◽

10.1007/978-3-030-66843-3_4 ◽

2020 ◽

pp. 34-44

Author(s):

Naresh Nandakumar ◽

Niharika Shimona D’Souza ◽

Komal Manzoor ◽

Jay J. Pillai ◽

Sachin K. Gujar ◽

...

Keyword(s):

Deep Learning ◽

Brain Tumor ◽

Functional Connectivity ◽

Tumor Patients ◽

Dynamic Functional Connectivity ◽

Learning Framework ◽

Eloquent Cortex

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SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science ◽

10.1007/978-3-030-66843-3_8 ◽

2020 ◽

pp. 77-87

Author(s):

Umar Asif ◽

Subhrajit Roy ◽

Jianbin Tang ◽

Stefan Harrer

Keyword(s):

Feature Learning ◽

Seizure Type ◽

Deep Feature ◽

Deep Feature Learning ◽

Type Classification

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Differentiation of Recurrent Glioblastoma from Radiation Necrosis Using Diffusion Radiomics: Machine Learning Model Development and External Validation

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science ◽

10.1007/978-3-030-66843-3_27 ◽

2020 ◽

pp. 276-283

Author(s):

Yae Won Park ◽

Ji Eun Park ◽

Sung Soo Ahn ◽

Hwiyoung Kim ◽

Ho Sung Kim ◽

...

Keyword(s):

Machine Learning ◽

Radiation Necrosis ◽

External Validation ◽

Model Development ◽

Learning Model ◽

Recurrent Glioblastoma ◽

Machine Learning Model

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Using Functional Magnetic Resonance Imaging and Personal Characteristics Features for Detection of Neurological Conditions

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science ◽

10.1007/978-3-030-66843-3_26 ◽

2020 ◽

pp. 268-275

Author(s):

Batool Rathore ◽

Muhammad Awais ◽

Muhammad Usama Usman ◽

Imran Shafi ◽

Waqas Ahmed

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Functional Magnetic Resonance Imaging ◽

Personal Characteristics ◽

Functional Magnetic Resonance ◽

Resonance Imaging ◽

Neurological Conditions

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Overall Survival Prediction in Gliomas Using Region-Specific Radiomic Features

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science ◽

10.1007/978-3-030-66843-3_25 ◽

2020 ◽

pp. 259-267

Author(s):

Asma Shaheen ◽

Stefano Burigat ◽

Ulas Bagci ◽

Hassan Mohy-ud-Din

Keyword(s):

Overall Survival ◽

Survival Prediction ◽

Overall Survival Prediction

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Multiple Sclerosis Lesion Segmentation Using Longitudinal Normalization and Convolutional Recurrent Neural Networks

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science ◽

10.1007/978-3-030-66843-3_15 ◽

2020 ◽

pp. 148-158

Author(s):

Sergio Tascon-Morales ◽

Stefan Hoffmann ◽

Martin Treiber ◽

Daniel Mensing ◽

Arnau Oliver ◽

...

Keyword(s):

Multiple Sclerosis ◽

Neural Networks ◽

Recurrent Neural Networks ◽

Multiple Sclerosis Lesion ◽

Lesion Segmentation

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Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science
Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Patch-Based Brain Age Estimation from MR Images

Deep Voxel-Guided Morphometry (VGM): Learning Regional Brain Changes in Serial MRI

Towards MRI Progression Features for Glioblastoma Patients: From Automated Volumetry and Classical Radiomics to Deep Feature Learning

Large-Scale Unbiased Neuroimage Indexing via 3D GPU-SIFT Filtering and Keypoint Masking

A Multi-task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity

SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification

Differentiation of Recurrent Glioblastoma from Radiation Necrosis Using Diffusion Radiomics: Machine Learning Model Development and External Validation

Using Functional Magnetic Resonance Imaging and Personal Characteristics Features for Detection of Neurological Conditions

Overall Survival Prediction in Gliomas Using Region-Specific Radiomic Features

Multiple Sclerosis Lesion Segmentation Using Longitudinal Normalization and Convolutional Recurrent Neural Networks

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Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Patch-Based Brain Age Estimation from MR Images

Deep Voxel-Guided Morphometry (VGM): Learning Regional Brain Changes in Serial MRI

Towards MRI Progression Features for Glioblastoma Patients: From Automated Volumetry and Classical Radiomics to Deep Feature Learning

Large-Scale Unbiased Neuroimage Indexing via 3D GPU-SIFT Filtering and Keypoint Masking

A Multi-task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity

SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification

Differentiation of Recurrent Glioblastoma from Radiation Necrosis Using Diffusion Radiomics: Machine Learning Model Development and External Validation

Using Functional Magnetic Resonance Imaging and Personal Characteristics Features for Detection of Neurological Conditions

Overall Survival Prediction in Gliomas Using Region-Specific Radiomic Features

Multiple Sclerosis Lesion Segmentation Using Longitudinal Normalization and Convolutional Recurrent Neural Networks

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Lecture Notes in Computer Science
Latest Publications