Book section icon

Book section : Chapter

Brain tumour segmentation using a triplanar ensemble of U-Nets on MR images

Abstract:

Gliomas appear with wide variation in their characteristics both in terms of their appearance and location on brain MR images, which makes robust tumour segmentation highly challenging, and leads to high inter-rater variability even in manual segmentations. In this work, we propose a triplanar ensemble network, with an independent tumour core prediction module, for accurate segmentation of these tumours and their sub-regions. On evaluating our method on the MICCAI Brain Tumor Segmentation (Br...

Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

Actions


Access Document


Files:
Publisher copy:
10.1007/978-3-030-72084-1_31

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Oxford college:
Somerville College
Role:
Author
ORCID:
0000-0002-9451-4779
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Author
ORCID:
0000-0002-0540-9353
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author
ORCID:
0000-0001-6043-0166
Publisher:
Springer Publisher's website
Volume:
12658
Pages:
340–353
Series:
Lecture Notes in Computer Science
Host title:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
Publication date:
2021-03-27
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
ISBN:
9783030720834
Language:
English
Keywords:
Subtype:
Chapter
Pubs id:
1169899
Local pid:
pubs:1169899
Deposit date:
2022-03-15

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP