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Segmentation of Pediatric Brain Tumors using a Radiologically informed, Deep Learning Cascade
Timothy Mulvany
,
Daniel Griffiths-King
,
Jan Novak
*
, Heather Rose
*
*
Corresponding author for this work
School of Psychology
Aston Institute of Health & Neurodevelopment
College of Engineering and Physical Sciences
Research output
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Preprint or Working paper
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Preprint
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Keyphrases
Deep Learning
100%
Pediatric Brain Tumor
100%
NnU-Net
100%
Brain Tumor Segmentation
62%
Tumor
25%
Encoder
25%
Segmentation Challenge
25%
Adaptation
12%
Segmentation Problem
12%
Substructure
12%
Multi-parameter
12%
Pediatric Patients
12%
Cascade Model
12%
Automated Approach
12%
Treatment Monitoring
12%
Volumetric Measurement
12%
Brain Tumor
12%
From Coarse to Fine
12%
Pediatric Neuro-oncology
12%
Quality Segmentation
12%
Dice Score
12%
Glioma Brain Tumor
12%
FLAIR MRI
12%
Robust Segmentation
12%
CE-FLAIR
12%
Cascade Learning
12%
Multiple Changes
12%
Diffuse Intrinsic Pontine Glioma
12%
Diffuse Midline Glioma
12%
Response Assessment
12%
T2-FLAIR
12%
Neuroscience
Intracranial Tumor
100%
Pediatric Brain Tumor
100%
Magnetic Resonance Imaging
50%
Pediatric Neurology
16%