Conference icon

Conference

Unsupervised segmentation of MRI knees using Image Partition Forests

Abstract:

Nowadays many people are affected by arthritis, a condition of the joints with limited prevention measures, but with various options of treatment the most radical of which is surgical. In order for surgery to be successful, it relies on careful analysis of patient–based models generated from medical images, usually by manual segmentation. In this work we show how to automate the segmentation of a crucial and complex joint – the knee. To achieve this goal we rely on our novel way of representi...

Expand abstract
Publication status:
In press
Peer review status:
Peer reviewed
Version:
Accepted manuscript

Actions


Access Document


Files:

Authors


More by this author
Institution:
University of Oxford
Department:
Oxford, MPLS, Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Department:
Oxford, MPLS, Computer Science
Role:
Author
Publisher:
Society of Photo-Optical Instrumentation Engineers (SPIE) Publisher's website
Volume:
Biomedical Applications in Molecular, Structural, and Functional Imaging
Publication date:
2016-03-05
ISSN:
1605-7422
URN:
uuid:000d2073-9081-4a5b-b238-021cc7178e49
Source identifiers:
595363
Local pid:
pubs:595363

Terms of use


Metrics


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