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Automated 3D Renal Segmentation Based on Image Partitioning

Abstract:

Despite several decades of research into segmentation techniques, automated medical image segmentation is barely usable in a clinical context, and still at vast user time expense. This paper illustrates unsupervised organ segmentation through the use of a novel automated labelling approximation algorithm followed by a hypersurface front propagation method. The approximation stage relies on a pre-computed image partition forest obtained directly from CT scan data. We have implemented all proce...

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Publication status:
In press
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
Publisher:
Society of Photo-Optical Instrumentation Engineers (SPIE) Publisher's website
Host title:
SPIE Medical Imaging
Publication date:
2016-03-01
Event location:
San Diego, California, United States
Event start date:
2016-02-27T00:00:00Z
ISSN:
0277-786X
Source identifiers:
595583
Pubs id:
pubs:595583
UUID:
uuid:1c62a952-7dc9-4b9e-920e-721a5db0283e
Local pid:
pubs:595583
Deposit date:
2016-01-29

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