Journal article icon

Journal article

Investigation of the role of feature selection and weighted voting in random forests for 3-D volumetric segmentation.

Abstract:

This paper describes a novel 3-D segmentation technique posed within the Random Forests (RF) classification framework. Two improvements over the traditional RF framework are considered. Motivated by the high redundancy of feature selection in the traditional RF framework, the first contribution develops methods to improve voxel classification by selecting relatively "strong" features and neglecting "weak" ones. The second contribution involves weighting each tree in the forest during the test...

Expand abstract
Publication status:
Published

Actions


Access Document


Publisher copy:
10.1109/tmi.2013.2284025

Authors


More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, NDORMS
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, NDORMS
Journal:
IEEE transactions on medical imaging
Volume:
33
Issue:
2
Pages:
258-271
Publication date:
2014-02-05
DOI:
EISSN:
1558-254X
ISSN:
0278-0062
URN:
uuid:b6de838d-5b6d-4f22-a2ea-91a6d17b6e1b
Source identifiers:
434233
Local pid:
pubs:434233

Terms of use


Metrics



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

TO TOP