- 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
- Publisher copy:
- 10.1109/tmi.2013.2284025
-
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- 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
- Language:
- English
- Keywords:
- Copyright date:
- 2014
Journal article
Investigation of the role of feature selection and weighted voting in random forests for 3-D volumetric segmentation.
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