Distinguishing between paediatric brain tumour types using multi-parametric magnetic resonance imaging and machine learning: A multi-site study-Reference-Cited by-同舟云学术

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Distinguishing between paediatric brain tumour types using multi-parametric magnetic resonance imaging and machine learning: A multi-site study

Published:2020 Issue: Volume:25 Page:102172
ISSN:2213-1582
Container-title:NeuroImage: Clinical
language:en
Short-container-title:NeuroImage: Clinical

Author:

Grist James T.^ORCID,Withey Stephanie,MacPherson Lesley,Oates Adam,Powell Stephen,Novak Jan^ORCID,Abernethy Laurence,Pizer Barry,Grundy Richard,Bailey Simon,Mitra Dipayan,Arvanitis Theodoros N.^ORCID,Auer Dorothee P.,Avula Shivaram,Peet Andrew C^ORCID

Funder

Cancer Research UK

NIHR Research Professorship

NIHR

EPSRC

Physical Sciences for Health Centre for Doctoral Training

UK

Medical Research Council

Department of Health and Social Care

Chief Scientist Office of the Scottish Government Health and Social Care Directorates

Health and Social Care Research and Development Division

Public Health Agency

British Heart Foundation and Wellcome Trust

Little Princess Trust

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology (clinical),Neurology,Radiology, Nuclear Medicine and imaging

Reference27 articles.

1. Discrimination of paediatric brain tumours using apparent diffusion coefficient histograms;Bull;Eur. Radiol.,2012

2. SMOTE : synthetic minority over-sampling technique;Chawla;J. Artif. Intell. Res.,2002

3. Machine learning for medical imaging;Erickson;Radiographics,2017

4. Magnetic resonance spectroscopy and its clinical applications: a review;Faghihi;J. Med. Imaging Radiat. Sci.,2017

5. Radiomics in paediatric neuro-oncology: a multicentre study on MRI texture analysis;Fetit;NMR Biomed.,2018

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