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Accurate brain‐age models for routine clinical MRI examinations

NeuroImage (Orlando, Fla.), 2022-04, Vol.249, p.118871-118871, Article 118871

2022

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Editorial: Rising stars in neuroradiology: 2022

Frontiers in radiology, 2024-01, Vol.3, p.1349600-1349600

Booth, Thomas C

2024

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Artificial intelligence in the autonomous navigation of endovascular interventions: a systematic review

Frontiers in human neuroscience, 2023-08, Vol.17, p.1239374-1239374

2023

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High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Frontiers in oncology, 2022-03, Vol.12, p.810263-810263

2022

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Analysis of heterogeneity in T2-weighted MR images can differentiate pseudoprogression from progression in glioblastoma

PloS one, 2017-05, Vol.12 (5), p.e0176528-e0176528

2017

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The current impact of incidental findings found during neuroimaging on neurologists' workloads

PloS one, 2015-02, Vol.10 (2), p.e0118155-e0118155

2015

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Imaging Biomarkers of Glioblastoma Treatment Response: A Systematic Review and Meta-Analysis of Recent Machine Learning Studies

Frontiers in oncology, 2022-01, Vol.12, p.799662

2022

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High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics

Frontiers in oncology, 2022-02, Vol.11, p.811425-811425

2022

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SurvNet: A low-complexity convolutional neural network for survival time classification of patients with glioblastoma

Heliyon, 2024-06, Vol.10 (12), p.e32870, Article e32870

2024

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Incidental findings on imaging

BMJ (Online), 2018-06, Vol.361, p.k2611

Booth, Thomas C

2018

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Analysis of image heterogeneity using 2D Minkowski functionals detects tumor responses to treatment

Magnetic resonance in medicine, 2014-01, Vol.71 (1), p.402-410

2014

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The changing landscape of cerebral revascularization surgery: A United Kingdom experience

Frontiers in radiology, 2022-09, Vol.2, p.981501-981501

2022

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Factors affecting the labelling accuracy of brain MRI studies relevant for deep learning abnormality detection

Frontiers in radiology, 2023-11, Vol.3, p.1251825-1251825

2023

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Editorial for “Apparent Diffusion Coefficient as Imaging Biomarker for Identifying IDH Mutation, 1p19q Codeletion, and MGMT Promoter Methylation Status in Patients With Glioma”

Journal of magnetic resonance imaging, 2023-09, Vol.58 (3), p.739-740

2023

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Detection of cerebral aneurysms using artificial intelligence: a systematic review and meta-analysis

Journal of neurointerventional surgery, 2023-03, Vol.15 (3), p.262

2023

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Autonomous navigation of catheters and guidewires in mechanical thrombectomy using inverse reinforcement learning

International journal for computer assisted radiology and surgery, 2024-06

2024

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Systematic Review of Artificial Intelligence for Abnormality Detection in High-volume Neuroimaging and Subgroup Meta-analysis for Intracranial Hemorrhage Detection

Clinical neuroradiology (Munich), 2023-12, Vol.33 (4), p.943-956

2023

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Glioblastoma post-operative imaging in neuro-oncology: current UK practice (GIN CUP study)

European radiology, 2021-05, Vol.31 (5), p.2933-2943

2021

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The experience of interval scans for adults living with primary malignant brain tumors

Supportive care in cancer, 2023-06, Vol.31 (6), p.356-356, Article 356

2023

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Incidental findings discovered during imaging: implications for general practice

British journal of general practice, 2016-07, Vol.66 (648), p.346-347

2016

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Robotics in neurointerventional surgery: a systematic review of the literature

Journal of neurointerventional surgery, 2022-06, Vol.14 (6), p.539

2022

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Deep learning to automate the labelling of head MRI datasets for computer vision applications

European radiology, 2022-01, Vol.32 (1), p.725-736

2022

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Optimising brain age estimation through transfer learning: A suite of pre‐trained foundation models for improved performance and generalisability in a clinical setting

Human brain mapping, 2024-03, Vol.45 (4), p.e26625-n/a

2024

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Accurate brain‐age models for routine clinical MRI examinations

Editorial: Rising stars in neuroradiology: 2022

Artificial intelligence in the autonomous navigation of endovascular interventions: a systematic review

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Analysis of heterogeneity in T2-weighted MR images can differentiate pseudoprogression from progression in glioblastoma

The current impact of incidental findings found during neuroimaging on neurologists' workloads

Imaging Biomarkers of Glioblastoma Treatment Response: A Systematic Review and Meta-Analysis of Recent Machine Learning Studies

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics

SurvNet: A low-complexity convolutional neural network for survival time classification of patients with glioblastoma

Incidental findings on imaging

Analysis of image heterogeneity using 2D Minkowski functionals detects tumor responses to treatment

A Position Statement on the Utility of Interval Imaging in Standard of Care Brain Tumour Management: Defining the Evidence Gap and Opportunities for Future Research

The changing landscape of cerebral revascularization surgery: A United Kingdom experience

Factors affecting the labelling accuracy of brain MRI studies relevant for deep learning abnormality detection

Editorial for “Apparent Diffusion Coefficient as Imaging Biomarker for Identifying IDH Mutation, 1p19q Codeletion, and MGMT Promoter Methylation Status in Patients With Glioma”

Detection of cerebral aneurysms using artificial intelligence: a systematic review and meta-analysis

Autonomous navigation of catheters and guidewires in mechanical thrombectomy using inverse reinforcement learning

Systematic Review of Artificial Intelligence for Abnormality Detection in High-volume Neuroimaging and Subgroup Meta-analysis for Intracranial Hemorrhage Detection

Glioblastoma post-operative imaging in neuro-oncology: current UK practice (GIN CUP study)

The experience of interval scans for adults living with primary malignant brain tumors

Incidental findings discovered during imaging: implications for general practice

Robotics in neurointerventional surgery: a systematic review of the literature

Deep learning to automate the labelling of head MRI datasets for computer vision applications

Optimising brain age estimation through transfer learning: A suite of pre‐trained foundation models for improved performance and generalisability in a clinical setting

Perfusion Imaging for Endovascular Thrombectomy in Acute Ischemic Stroke Is Associated With Improved Functional Outcomes in the Early and Late Time Windows

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